how to write a hypothesis in geometry

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Conditional Statement If Then's Defined in Geometry - 15+ Examples!

// Last Updated: January 21, 2020 - Watch Video //

In today’s geometry lesson , you’re going to learn all about conditional statements!

Jenn, Founder Calcworkshop ® , 15+ Years Experience (Licensed & Certified Teacher)

We’re going to walk through several examples to ensure you know what you’re doing.

In addition, this lesson will prepare you for deductive reasoning and two column proofs later on.

Here we go!

What are Conditional Statements?

To better understand deductive reasoning, we must first learn about conditional statements.

A conditional statement has two parts: hypothesis ( if ) and conclusion ( then ).

In fact, conditional statements are nothing more than “If-Then” statements!

Sometimes a picture helps form our hypothesis or conclusion. Therefore, we sometimes use Venn Diagrams to visually represent our findings and aid us in creating conditional statements.

But to verify statements are correct, we take a deeper look at our if-then statements. This is why we form the converse , inverse , and contrapositive of our conditional statements.

What is the Converse of a Statement?

Well, the converse is when we switch or interchange our hypothesis and conclusion.

Conditional Statement : “If today is Wednesday, then yesterday was Tuesday.”

Hypothesis : “If today is Wednesday” so our conclusion must follow “Then yesterday was Tuesday.”

So the converse is found by rearranging the hypothesis and conclusion, as Math Planet accurately states.

Converse : “If yesterday was Tuesday, then today is Wednesday.”

What is the Inverse of a Statement?

Now the inverse of an If-Then statement is found by negating (making negative) both the hypothesis and conclusion of the conditional statement.

So using our current conditional statement, “If today is Wednesday, then yesterday was Tuesday”.

Inverse : “If today is not Wednesday, then yesterday was not Tuesday.”

What is a Contrapositive?

And the contrapositive is formed by interchanging the hypothesis and conclusion and then negating both.

Contrapositive : “If yesterday was not Tuesday, then today is not Wednesday”

What is a Biconditional Statement?

A statement written in “if and only if” form combines a reversible statement and its true converse. In other words the conditional statement and converse are both true.

Continuing with our initial condition, “If today is Wednesday, then yesterday was Tuesday.”

Biconditional : “Today is Wednesday if and only if yesterday was Tuesday.”

Examples of Conditional Statements

In the video below we will look at several harder examples of how to form a proper statement, converse, inverse, and contrapositive. And here’s a big hint…

Whenever you see “con” that means you switch! It’s like being a con-artist!

Moreover, we will detail the process for coming up with reasons for our conclusions using known postulates. We will review the ten postulates that we have learned so far, and add a few more problems dealing with perpendicular lines, planes, and perpendicular bisectors.

After this lesson, we will be ready to tackle deductive reasoning head-on, and feel confident as we march onward toward learning two-column proofs!

Conditional Statements – Lesson & Examples (Video)

• Introduction to conditional statements
• 00:00:25 – What are conditional statements, converses, and biconditional statements? (Examples #1-2)
• 00:05:21 – Understanding venn diagrams (Examples #3-4)
• 00:11:07 – Supply the missing venn diagram and conditional statement for each question (Examples #5-8)
• Exclusive Content for Member’s Only
• 00:17:48 – Write the statement and converse then determine if they are reversible (Examples #9-12)
• 00:29:17 – Understanding the inverse, contrapositive, and symbol notation
• 00:35:33 – Write the statement, converse, inverse, contrapositive, and biconditional statements for each question (Examples #13-14)
• 00:45:40 – Using geometry postulates to verify statements (Example #15)
• 00:53:23 – What are perpendicular lines, perpendicular planes and the perpendicular bisector?
• 00:56:26 – Using the figure, determine if the statement is true or false (Example #16)
• Practice Problems with Step-by-Step Solutions
• Chapter Tests with Video Solutions

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If-then statement

• Logical correct I
• Logical correct II

When we previously discussed inductive reasoning we based our reasoning on examples and on data from earlier events. If we instead use facts, rules and definitions then it's called deductive reasoning.

We will explain this by using an example.

If you get good grades then you will get into a good college.

The part after the "if": you get good grades - is called a hypotheses and the part after the "then" - you will get into a good college - is called a conclusion.

Hypotheses followed by a conclusion is called an If-then statement or a conditional statement.

This is noted as

$$p \to q$$

This is read - if p then q.

A conditional statement is false if hypothesis is true and the conclusion is false. The example above would be false if it said "if you get good grades then you will not get into a good college".

If we re-arrange a conditional statement or change parts of it then we have what is called a related conditional.

Our conditional statement is: if a population consists of 50% men then 50% of the population must be women.

If we exchange the position of the hypothesis and the conclusion we get a converse statemen t: if a population consists of 50% women then 50% of the population must be men.

$$q\rightarrow p$$

If both statements are true or if both statements are false then the converse is true. A conditional and its converse do not mean the same thing

If we negate both the hypothesis and the conclusion we get a inverse statemen t: if a population do not consist of 50% men then the population do not consist of 50% women.

$$\sim p\rightarrow \: \sim q$$

The inverse is not true juest because the conditional is true. The inverse always has the same truth value as the converse.

We could also negate a converse statement, this is called a contrapositive statemen t:  if a population do not consist of 50% women then the population do not consist of 50% men.

$$\sim q\rightarrow \: \sim p$$

The contrapositive does always have the same truth value as the conditional. If the conditional is true then the contrapositive is true.

A pattern of reaoning is a true assumption if it always lead to a true conclusion. The most common patterns of reasoning are detachment and syllogism.

If we turn of the water in the shower, then the water will stop pouring.

If we call the first part p and the second part q then we know that p results in q. This means that if p is true then q will also be true. This is called the law of detachment and is noted:

$$\left [ (p \to q)\wedge p \right ] \to q$$

The law of syllogism tells us that if p → q and q → r then p → r is also true.

This is noted:

$$\left [ (p \to q)\wedge (q \to r ) \right ] \to (p \to r)$$

If the following statements are true:

If we turn of the water (p), then the water will stop pouring (q). If the water stops pouring (q) then we don't get wet any more (r).

Then the law of syllogism tells us that if we turn of the water (p) then we don't get wet (r) must be true.

Video lesson

Write a converse, inverse and contrapositive to the conditional

"If you eat a whole pint of ice cream, then you won't be hungry"

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Conditional Statements in Geometry

Conditional statements in geometry can be confusing for even the best geometry students. The logic and proof portion of your geometry curriculum is bursting with new terminology! There are conditional statements, and the inverse, converse, contrapositive, etc. And wait, we represent them with p’s and q’s?! Ok, let’s break it down. 

What is a Conditional Statement?

A conditional statement in geometry is an “if-then” statement.

The part of the statement that follows “if” is called the hypothesis , and the part of the statement that follows “then” is called the conclusion .

We also represent conditional statements symbolically. For a conditional statement, p represents the hypothesis and q represents the conclusion. Symbolically we write p → q, which reads “if p then q.”

Statements Related to the Conditional Statement

  Inverse . To write the inverse of the conditional statement, you negate the hypothesis AND conclusion. Symbolically, it’s written as ~p → ~q and read as “If not p, then not q”.

Converse . To write the converse of the conditional statement, you switch the hypothesis and conclusion. Symbolically, it’s written as q → p and read “if q then p”.

Contrapositive . To write the contrapositive of the conditional statement, you both negate AND switch the hypothesis and conclusion. Symbolically, it’s written as ~q → ~p and read “if not q, then not p”. 

Resources for Teaching Conditional Statements

Looking for a graphic organizer to summarize conditional statements in geometry? Leave me your e-mail and I’ll send you one for FREE!  

Students can practice writing statements and determining their truth value with this self-checking assignment ! 

Stay tuned for a Logic and Proof Unit Bundle coming soon! 

Happy teaching!

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Methodology

• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1. ask a question.

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in  if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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Difference between axioms, theorems, postulates, corollaries, and hypotheses

I've heard all these terms thrown about in proofs and in geometry, but what are the differences and relationships between them? Examples would be awesome! :)

• terminology

• 3 $\begingroup$ Go read this Wikipedia article and the articles it links to. $\endgroup$ –  kahen Commented Oct 24, 2010 at 20:22
• 10 $\begingroup$ One difficulty is that, for historical reasons, various results have a specific term attached (Parallel postulate, Zorn's lemma, Riemann hypothesis, Collatz conjecture, Axiom of determinacy). These do not always agree with the the usual usage of the words. Also, some theorems have unique names, for example Hilbert's Nullstellensatz. Since the German word there incorporates "satz", which means "theorem", it is not typical to call this the "Nullstellensatz theorem". These things make it harder to pick up the general usage. $\endgroup$ –  Carl Mummert Commented Oct 24, 2010 at 23:15

5 Answers 5

In Geometry, " Axiom " and " Postulate " are essentially interchangeable. In antiquity, they referred to propositions that were "obviously true" and only had to be stated, and not proven. In modern mathematics there is no longer an assumption that axioms are "obviously true". Axioms are merely 'background' assumptions we make. The best analogy I know is that axioms are the "rules of the game". In Euclid's Geometry, the main axioms/postulates are:

• Given any two distinct points, there is a line that contains them.
• Any line segment can be extended to an infinite line.
• Given a point and a radius, there is a circle with center in that point and that radius.
• All right angles are equal to one another.
• If a straight line falling on two straight lines makes the interior angles on the same side less than two right angles, the two straight lines, if produced indefinitely, meet on that side on which are the angles less than the two right angles. (The parallel postulate ).

A theorem is a logical consequence of the axioms. In Geometry, the "propositions" are all theorems: they are derived using the axioms and the valid rules. A "Corollary" is a theorem that is usually considered an "easy consequence" of another theorem. What is or is not a corollary is entirely subjective. Sometimes what an author thinks is a 'corollary' is deemed more important than the corresponding theorem. (The same goes for " Lemma "s, which are theorems that are considered auxiliary to proving some other, more important in the view of the author, theorem).

A " hypothesis " is an assumption made. For example, "If $x$ is an even integer, then $x^2$ is an even integer" I am not asserting that $x^2$ is even or odd; I am asserting that if something happens (namely, if $x$ happens to be an even integer) then something else will also happen. Here, "$x$ is an even integer" is the hypothesis being made to prove it.

See the Wikipedia pages on axiom , theorem , and corollary . The first two have many examples.

• 2 $\begingroup$ Arturo, I hope you don't mind if I edged your already excellent answer a little bit nearer to perfection. $\endgroup$ –  J. M. ain't a mathematician Commented Oct 25, 2010 at 0:26
• $\begingroup$ @J.M.: Heh. Not at all; thanks for the corrections! You did miss the single quotation mark after "propositions" in the second paragraph, though. (-: $\endgroup$ –  Arturo Magidin Commented Oct 25, 2010 at 0:33
• $\begingroup$ Great answer. Clear and informal, while still accurate. Better than wikipedia's, in my opinion. $\endgroup$ –  7hi4g0 Commented Feb 8, 2014 at 0:47
• $\begingroup$ Why is Bertrand's postulate considered a postulate? I don't think it would be obvious to anybody except to extraordinary geniuses like Euler, Gauss or Ramanujan.. $\endgroup$ –  AvZ Commented Feb 14, 2015 at 5:54
• 1 $\begingroup$ @gen-zreadytoperish: People don’t use usually use “postulate” anymore outside of historical contexts (e.g., “Bertrand’s postulate”). $\endgroup$ –  Arturo Magidin Commented Apr 12, 2020 at 20:26

Based on logic, an axiom or postulate is a statement that is considered to be self-evident. Both axioms and postulates are assumed to be true without any proof or demonstration. Basically, something that is obvious or declared to be true and accepted but have no proof for that, is called an axiom or a postulate. Axioms and postulate serve as a basis for deducing other truths.

The ancient Greeks recognized the difference between these two concepts. Axioms are self-evident assumptions, which are common to all branches of science, while postulates are related to the particular science.

Aristotle by himself used the term “axiom”, which comes from the Greek “axioma”, which means “to deem worth”, but also “to require”. Aristotle had some other names for axioms. He used to call them as “the common things” or “common opinions”. In Mathematics, Axioms can be categorized as “Logical axioms” and “Non-logical axioms”. Logical axioms are propositions or statements, which are considered as universally true. Non-logical axioms sometimes called postulates, define properties for the domain of specific mathematical theory, or logical statements, which are used in deduction to build mathematical theories. “Things which are equal to the same thing, are equal to one another” is an example for a well-known axiom laid down by Euclid.

The term “postulate” is from the Latin “postular”, a verb which means “to demand”. The master demanded his pupils that they argue to certain statements upon which he could build. Unlike axioms, postulates aim to capture what is special about a particular structure. “It is possible to draw a straight line from any point to any other point”, “It is possible to produce a finite straight continuously in a straight line”, and “It is possible to describe a circle with any center and any radius” are few examples for postulates illustrated by Euclid.

What is the difference between Axioms and Postulates?

• An axiom generally is true for any field in science, while a postulate can be specific on a particular field.

• It is impossible to prove from other axioms, while postulates are provable to axioms.

• $\begingroup$ Hmmm. This isn't a bad explanation, and thanks for attempting to explain the difference, but I'm still a bit fuzzy on the historical distinction as used by Aristotle and Euclid. $\endgroup$ –  Wildcard Commented Dec 10, 2016 at 2:53
• $\begingroup$ The historical part is interesting but at the end your statements are not correct. It is not the way the words "axiom" and "postulate" are being used in math and logic. $\endgroup$ –  LoMaPh Commented Jun 18, 2017 at 9:16

Technically Axioms are self-evident or self-proving, while postulates are simply taken as given. However really only Euclid and really high end theorists and some poly-maths make such a distinction. See http://www.friesian.com/space.htm

Theorems are then derived from the "first principles" i.e. the axioms and postulates.

• 3 $\begingroup$ No, that "technical" division really leads nowhere, and nowadays no one follows it. $\endgroup$ –  Andrés E. Caicedo Commented Nov 23, 2014 at 17:58
• 2 $\begingroup$ From a purely epistemological standpoint this is an excellent distinction, and I am extremely glad you took the time to contribute this simple answer. This fully clarified the historical difference for me. While @AndrésE.Caicedo is correct that this distinction doesn't form a part of modern mathematical practice, that doesn't make it wholly valueless. $\endgroup$ –  Wildcard Commented Dec 10, 2016 at 3:03

Axiom: Not proven and known to be unprovable using other axioms

Postulate: Not proven but not known if it can be proven from axioms (and theorems derived only from axioms)

Theorem: Proved using axioms and postulates

For example -- the parallel postulate of Euclid was used unproven but for many millennia a proof was thought to exist for it in terms of other axioms. Later is was definitively shown that it could not (by e.g. showing consistent other geometries). At that point it could be converted to axiom status for the Euclidean geometric system.

I think everything being marked as postulates is a bit of a disservice, but also reflect it would be almost impossible to track if any nontrivial theorem does not somewhere depend on a postulate rather than an axiom, also, standards for what constitutes 'proof' changes over time.

But I do think the triple structure is helpful for teaching beginning students. E.g. you can prove congruence of triangles via SSS with some axioms but it can be damnably hard and confusing/circular/nit-picky, so it makes sense to teach it as a postulate at first, use it, and then come back and show a proof.

• $\begingroup$ I think that the common usage does not require that an axiom is "known to be unprovable using other axioms." This would mean that there is no such thing as "an axiom", only "an axiom relative to other statements"; and it would mean that many common presentations of axioms actually don't consist of axioms. (For example, the axioms of a ring include left and right distributivity of multiplication over addition; the axioms of a commutative ring include commutativity of multiplication; but suddenly that means that we must (arbitrarily) pick only left or right distributivity as an axiom.) $\endgroup$ –  LSpice Commented Mar 6, 2018 at 14:39

Since it is not possible to define everything, as it leads to a never ending infinite loop of circular definitions, mathematicians get out of this problem by imposing "undefined terms". Words we never define. In most mathematics that two undefined terms are set and element of .

We would like to be able prove various things concerning sets. But how can we do so if we never defined what a set is? So what mathematicians do next is impose a list of axioms . An axiom is some property of your undefined object. So even though you never define your undefined terms you have rules about them. The rules that govern them are the axioms . One does not prove an axiom, in fact one can choose it to be anything he wishes (of course, if it is done mindlessly it will lead to something trivial).

Now that we have our axioms and undefined terms we can form some main definitions for what we want to work with.

After we defined some stuff we can write down some basic proofs. Usually known as propositions . Propositions are those mathematical facts that are generally straightforward to prove and generally follow easily form the definitions.

Deep propositions that are an overview of all your currently collected facts are usually called Theorems . A good litmus test, to know the difference between a Proposition and Theorem, as somebody once remarked here, is that if you are proud of a proof you call it a Theorem, otherwise you call it a Proposition. Think of a theorem as the end goals we would like to get, deep connections that are also very beautiful results.

Sometimes in proving a Proposition or a Theorem we need some technical facts. Those are called Lemmas . Lemmas are usually not useful by themselves. They are only used to prove a Proposition/Theorem, and then we forget about them.

The net collection of definitions, propositions, theorems, form a mathematical theory .

• 1 $\begingroup$ Please don't propound the falsehood that "it is not possible to define everything." I understand what you mean by it, but the result is only pedagogical disaster. (See my answer here.) The truth is that a concept or thought is a distinct entity from a symbolic representation, and when a concept is grasped directly, total understanding is possible in spite of the apparent circularity of defining words using other words. $\endgroup$ –  Wildcard Commented Dec 10, 2016 at 2:58

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How to Do Proofs in Geometry – Mastering Shapes and Theorems with Ease

JUMP TO TOPIC

Approaching Proofs in Geometry

Similarity and congruence, algebraic techniques, intuition in proofs.

To do proofs in geometry, I start by understanding the fundamental logic that forms the basis for all mathematical reasoning.

Geometry is the branch of mathematics that deals with the properties and relations of points, lines, angles, surfaces, and solids.

Proving a geometrical statement requires a set of logical steps that lead to a conclusion based on given, known facts and previously established theorems.

As someone keen to study or teach geometry, it’s essential to comprehend how to construct a logical sequence of statements to arrive at a geometric truth.

Proof in geometry often begins by identifying the information provided in a problem and gathering any relevant theorems or definitions that apply to the situation. It’s a meticulous process that involves presenting arguments systematically.

Using deductive reasoning, each step in the proof builds off the previous ones, ensuring there is a clear and direct line of thought from the initial assumptions to the final conclusion.

This practice not only solidifies my understanding of geometric concepts but also sharpens my analytical skills.

Crafting a convincing geometric proof is akin to putting together a puzzle where each piece must fit perfectly. I always remind myself to pay attention to detail and embrace the challenge; every proof solved is a new victory in the conquest of mathematical mastery.

When I start a geometry proof, my first step is always to understand the problem . I identify and list all the given information , such as angles , sides , and properties of triangles or parallel lines .

Getting a clear visual of the figure is crucial, so I often draw it out or refer to it frequently.

I use vocabulary like congruent , perpendicular , or similar as needed. The congruent triangles and the reflexive property can help me relate different parts of the figure . Here are some key elements to remember:

• Statements and reasons : Organize your proof with each statement supported by a reason.
• The Segment Addition Postulate ($AB + BC = AC$ if $B$ is between $A$ and $C$) and the Angle Addition Postulate are foundational tools.

The structure of the proof is also important. I may use a two-column proof , where one column lists statements and the other lists the reasons in parallel. Alternatively, I may use a paragraph proof , which combines statements and reasons into flowing text.

Here’s a simple framework of how I typically format:

My proofs rely on theorems and postulates such as the Angle Bisector Theorem or parallel lines creating congruent alternate interior angles . Recognizing patterns of congruent angles and congruent sides in isosceles triangles or parallelograms can also guide my reasoning.

Lastly, the concept of CPCTC (Corresponding Parts of Congruent Triangles are Congruent ) often serves as a critical final link in proving parts of a triangle are congruent by first proving the triangles are congruent.

Remember, patience and practice are key in mastering geometry proofs . The path from problem to conclusion can be challenging but rewarding.

Advanced Proof Techniques

When tackling advanced geometry proofs, I incorporate a variety of strategies that account for similarity , algebra , angle congruence , and intuition . My approach allows me to systematically address complex problems.

I always begin by identifying any similar figures, which share the same shape but may differ in size, using the AA (Angle-Angle) postulate:

• AAA (Angle-Angle-Angle) is not sufficient for similarity because it doesn’t consider proportionality.

I then consider angle congruence and side ratios, setting up proportions like $\frac{AB}{A’B’} = \frac{BC}{B’C’}$ when figures ABC and A’B’C’ are similar .

Algebra is a powerful ally in geometry proofs. I make use of substitution and rearranging equations to isolate variables, employing properties like the Distributive Property $(a(b+c) = ab+ac)$ to simplify complex expressions.

My intuition guides me toward relevant theorems and postulates. For instance, I know to consider the Pythagorean theorem when dealing with right triangles, recognizing when $a^2 + b^2 = c^2$ can be applied.

By integrating these techniques thoughtfully, I construct robust proofs that stand on a solid foundation of geometry principles.

In geometry, writing a solid proof is akin to presenting a persuasive argument; the goal is to show beyond doubt that a specific conclusion is true.

When I approach this final stage, my focus is on ensuring that every step from my premises to my ultimate claim is backed by rigorous logic and mathematical principles.

Firstly, I like to make a checklist to verify that my proof includes all necessary components. Do I have my givens ? Are my theorems and definitions accurately applied?

Did I ensure that every statement in my proof is justified, either by a given, definition, a postulate, or a previously proven theorem? These questions are crucial checkpoints before finalizing my argument.

To illustrate, if my goal is to prove that two lines are parallel, I need to demonstrate that, given a transversal, alternate interior angles are equal; this relies on the Alternate Interior Angles Theorem which asserts that if $ \angle A \cong \angle B $, then line $ l_1 \parallel l_2 $.

In essence, the conclusion of a geometric proof is the culmination of careful analysis and logical reasoning. It ties back to the initial givens and follows through each statement methodically until the final assertion is made.

To be effective, the proof should lead the reader seamlessly through my thought process, leaving no gaps or ambiguities. Ultimately, in a successful geometry proof, every claim is substantiated, and the conclusion resonates with certainty and clarity.

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Published 2008 Revised 2019

Understanding Hypotheses

'What happens if ... ?' to ' This will happen if'

The experimentation of children continually moves on to the exploration of new ideas and the refinement of their world view of previously understood situations. This description of the playtime patterns of young children very nicely models the concept of 'making and testing hypotheses'. It follows this pattern:

• Make some observations. Collect some data based on the observations.
• Draw a conclusion (called a 'hypothesis') which will explain the pattern of the observations.
• Test out your hypothesis by making some more targeted observations.

So, we have

• A hypothesis is a statement or idea which gives an explanation to a series of observations.

Sometimes, following observation, a hypothesis will clearly need to be refined or rejected. This happens if a single contradictory observation occurs. For example, suppose that a child is trying to understand the concept of a dog. He reads about several dogs in children's books and sees that they are always friendly and fun. He makes the natural hypothesis in his mind that dogs are friendly and fun . He then meets his first real dog: his neighbour's puppy who is great fun to play with. This reinforces his hypothesis. His cousin's dog is also very friendly and great fun. He meets some of his friends' dogs on various walks to playgroup. They are also friendly and fun. He is now confident that his hypothesis is sound. Suddenly, one day, he sees a dog, tries to stroke it and is bitten. This experience contradicts his hypothesis. He will need to amend the hypothesis. We see that

• Gathering more evidence/data can strengthen a hypothesis if it is in agreement with the hypothesis.
• If the data contradicts the hypothesis then the hypothesis must be rejected or amended to take into account the contradictory situation.

• A contradictory observation can cause us to know for certain that a hypothesis is incorrect.
• Accumulation of supporting experimental evidence will strengthen a hypothesis but will never let us know for certain that the hypothesis is true.

In short, it is possible to show that a hypothesis is false, but impossible to prove that it is true!

Whilst we can never prove a scientific hypothesis to be true, there will be a certain stage at which we decide that there is sufficient supporting experimental data for us to accept the hypothesis. The point at which we make the choice to accept a hypothesis depends on many factors. In practice, the key issues are

• What are the implications of mistakenly accepting a hypothesis which is false?
• What are the cost / time implications of gathering more data?
• What are the implications of not accepting in a timely fashion a true hypothesis?

For example, suppose that a drug company is testing a new cancer drug. They hypothesise that the drug is safe with no side effects. If they are mistaken in this belief and release the drug then the results could have a disastrous effect on public health. However, running extended clinical trials might be very costly and time consuming. Furthermore, a delay in accepting the hypothesis and releasing the drug might also have a negative effect on the health of many people.

In short, whilst we can never achieve absolute certainty with the testing of hypotheses, in order to make progress in science or industry decisions need to be made. There is a fine balance to be made between action and inaction.

Hypotheses and mathematics So where does mathematics enter into this picture? In many ways, both obvious and subtle:

• A good hypothesis needs to be clear, precisely stated and testable in some way. Creation of these clear hypotheses requires clear general mathematical thinking.
• The data from experiments must be carefully analysed in relation to the original hypothesis. This requires the data to be structured, operated upon, prepared and displayed in appropriate ways. The levels of this process can range from simple to exceedingly complex.

Very often, the situation under analysis will appear to be complicated and unclear. Part of the mathematics of the task will be to impose a clear structure on the problem. The clarity of thought required will actively be developed through more abstract mathematical study. Those without sufficient general mathematical skill will be unable to perform an appropriate logical analysis.

Using deductive reasoning in hypothesis testing

There is often confusion between the ideas surrounding proof, which is mathematics, and making and testing an experimental hypothesis, which is science. The difference is rather simple:

• Mathematics is based on deductive reasoning : a proof is a logical deduction from a set of clear inputs.
• Science is based on inductive reasoning : hypotheses are strengthened or rejected based on an accumulation of experimental evidence.

Of course, to be good at science, you need to be good at deductive reasoning, although experts at deductive reasoning need not be mathematicians. Detectives, such as Sherlock Holmes and Hercule Poirot, are such experts: they collect evidence from a crime scene and then draw logical conclusions from the evidence to support the hypothesis that, for example, Person M. committed the crime. They use this evidence to create sufficiently compelling deductions to support their hypotheses beyond reasonable doubt . The key word here is 'reasonable'. There is always the possibility of creating an exceedingly outlandish scenario to explain away any hypothesis of a detective or prosecution lawyer, but judges and juries in courts eventually make the decision that the probability of such eventualities are 'small' and the chance of the hypothesis being correct 'high'.

• If a set of data is normally distributed with mean 0 and standard deviation 0.5 then there is a 97.7% certainty that a measurement will not exceed 1.0.
• If the mean of a sample of data is 12, how confident can we be that the true mean of the population lies between 11 and 13?

It is at this point that making and testing hypotheses becomes a true branch of mathematics. This mathematics is difficult, but fascinating and highly relevant in the information-rich world of today.

To read more about the technical side of hypothesis testing, take a look at What is a Hypothesis Test?

You might also enjoy reading the articles on statistics on the Understanding Uncertainty website

This resource is part of the collection Statistics - Maths of Real Life

Definition Of Hypothesis

Hypothesis is the part of a conditional statement just after the word if.

Examples of Hypothesis

In the conditional, "If all fours sides of a quadrilateral measure the same, then the quadrilateral is a square" the hypothesis is "all fours sides of a quadrilateral measure the same".

Video Examples: Hypothesis  

Solved Example on Hypothesis

Ques:  in the example above, is the hypothesis "all fours sides of a quadrilateral measure the same" always, never, or sometimes true.

A. always B. never C. sometimes Correct Answer: C

Step 1: The hypothesis is sometimes true. Because, its true only for a square and a rhombus, not for the other quadrilaterals rectangle, parallelogram, or trapezoid.

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• Identifying-and-Describing-Right-Triangles-Gr-4
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• Two-dimensional-Geometric-Figures-Gr-4
• Interpreting-Multiplication-as-Scaling-or-Resizing-Gr-5
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Right Triangles

Rules, Formula and more

Pythagorean Theorem

The sum of the squares of the lengths of the legs equals the square of the length of the hypotenuse .

Usually, this theorem is expressed as $$ A^2 + B^2 = C^2 $$ .

Right Triangle Properties

A right triangle has one $$ 90^{\circ} $$ angle ($$ \angle $$ B in the picture on the left) and a variety of often-studied formulas such as:

• The Pythagorean Theorem
• Trigonometry Ratios (SOHCAHTOA)
• Pythagorean Theorem vs Sohcahtoa (which to use)

SOHCAHTOA only applies to right triangles ( more here ) .

A Right Triangle's Hypotenuse

The hypotenuse is the largest side in a right triangle and is always opposite the right angle.

In the triangle above, the hypotenuse is the side AB which is opposite the right angle, $$ \angle C $$.

Online tool calculates the hypotenuse (or a leg) using the Pythagorean theorem.

Practice Problems

Below are several practice problems involving the Pythagorean theorem, you can also get more detailed lesson on how to use the Pythagorean theorem here .

Find the length of side t in the triangle on the left.

Substitute the two known sides into the Pythagorean theorem's formula : A² + B² = C²

What is the value of x in the picture on the left?

Set up the Pythagorean Theorem : 14 2 + 48 2 = x 2 2,500 = X 2

$$ x = \sqrt{2500} = 50 $$

$$ x^2 = 21^2 + 72^2 \\ x^2= 5625 \\ x = \sqrt{5625} \\ x =75 $$

Find the length of side X in the triangle on on the left?

Substitue the two known sides into the pythagorean theorem's formula : $$ A^2 + B^2 = C^2 \\ 8^2 + 6^2 = x^2 \\ x = \sqrt{100}=10 $$

What is x in the triangle on the left?

x 2 + 4 2 = 5 2 x 2 + 16 = 25 x 2 = 25 - 16 = 9 x = 3

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5.2 - writing hypotheses.

The first step in conducting a hypothesis test is to write the hypothesis statements that are going to be tested. For each test you will have a null hypothesis (\(H_0\)) and an alternative hypothesis (\(H_a\)).

When writing hypotheses there are three things that we need to know: (1) the parameter that we are testing (2) the direction of the test (non-directional, right-tailed or left-tailed), and (3) the value of the hypothesized parameter.

• At this point we can write hypotheses for a single mean (\(\mu\)), paired means(\(\mu_d\)), a single proportion (\(p\)), the difference between two independent means (\(\mu_1-\mu_2\)), the difference between two proportions (\(p_1-p_2\)), a simple linear regression slope (\(\beta\)), and a correlation (\(\rho\)). 
• The research question will give us the information necessary to determine if the test is two-tailed (e.g., "different from," "not equal to"), right-tailed (e.g., "greater than," "more than"), or left-tailed (e.g., "less than," "fewer than").
• The research question will also give us the hypothesized parameter value. This is the number that goes in the hypothesis statements (i.e., \(\mu_0\) and \(p_0\)). For the difference between two groups, regression, and correlation, this value is typically 0.

Hypotheses are always written in terms of population parameters (e.g., \(p\) and \(\mu\)).  The tables below display all of the possible hypotheses for the parameters that we have learned thus far. Note that the null hypothesis always includes the equality (i.e., =).

• Math Article

In Mathematics, the term “Hypotenuse” comes from the Greek word  hypoteinousa  that means “stretching under”. This term is used in Geometry, especially in the right angle triangle. The longest side of a right-angle triangle is called the hypotenuse (the side which is opposite to the right angle). In this article, we are going to discuss the meaning of the term hypotenuse along with its formula, theorem, proof and examples.

Table of Contents:

Hypotenuse Meaning

• Hypotenuse of a Triangle
• Altitude to a Hypotenuse

Hypotenuse means, the longest side of a right-angled triangle compared to the length of the base and perpendicular. The hypotenuse side is opposite to the right angle, which is the biggest angle of all the three angles in a right triangle. Basically, the hypotenuse is the property of only the right triangle and no other triangle. Now, this is better explained when we learn about the right-angled theorem or  Pythagoras Theorem  or Pythagorean theorem. These concepts are majorly used in Trigonometry. Here, in this article, we will learn in detail about hypotenuse, its formula, theorem along with examples.

Hypotenuse Theorem

The hypotenuse theorem is defined by Pythagoras theorem, According to this theorem, the square of the hypotenuse side of a right-angled triangle is equal to the sum of squares of base and perpendicular of the same triangle, such that;

Hypotenuse 2 = Base 2 + Perpendicular 2

Hypotenuse Formula

The formula to find the hypotenuse is given by the square root of the sum of squares of base and perpendicular of a right-angled triangle. The hypotenuse formula can be expressed as;

Hypotenuse = √[Base 2 + Perpendicular 2 ]

Let a, b and c be the sides of the triangle as per given figure below;

So the hypotenuse formula for this triangle can be given as;

c 2 = a 2 + b 2

Where a is the perpendicular, b is the base and c is the hypotenuse.

Hypotenuse Theorem Proof

Given: A right triangle ABC, right-angled at B.

To Prove: Hypotenuse 2 = Base 2 + Perpendicular 2

Proof: In triangle ABC, let us draw a line from B to touch the side AC at D.

By similar triangles theorem, we can write;

△ADB ~ △ABC

So, AD/AB = AB/AC

Or AB 2 = AD x AC ………………..1

Again, △BDC ~△ABC

So, CD/BC = BC/AC

BC 2 = CD x AC ……………2

Now, if we add eq. 1 and 2 we get;

AB 2 + BC 2 = (AD x AC) + (CD x AC)

Taking AC as common term from right side, we get;

AB 2 + BC 2 = AC (AD + CD)

AB 2 + BC 2 = AC (AC)

AB 2 + BC 2 = AC 2

Base 2 + Perpendicular 2 = Hypotenuse 2

Hence, proved.

Hypotenuse of a triangle

The hypotenuse is only defined for the right-angled triangle. It is not defined for any other types of triangles in geometry such as

• Acute Angled Triangle
• Obtuse Angled Triangle
• Scalene Triangle
• Isosceles Triangle
• Equilateral Triangle

But only the isosceles triangle could be represented as a right-angled triangle, where the length of the base side and perpendicular side are equal and the third side will be the hypotenuse.

How to Find the Altitude on a Hypotenuse?

In Maths, the altitude of a triangle means the line segment that connects the vertex and the side opposite to the vertex. The length of the altitude is simply called the “altitude”. Similarly, the altitude to the hypotenuse is the line segment that connects the hypotenuse of a right triangle and the vertex opposite to the hypotenuse through the perpendicular. In elementary geometry, the relationship between the length of the altitude on the hypotenuse of a right triangle and the line segment created on the hypotenuse is explained using the theorem called the “Geometric Mean Theorem” or “Right Triangle Altitude Theorem”. The altitude to the hypotenuse can be found as follows:

Step 1: In a right triangle, draw the altitude of the hypotenuse. The altitude creates the two new right triangles which are similar to each other and the main right triangle.

Step 2: Now, divide the length of the shortest of the main right triangle by the hypotenuse of the main right triangle.

Step 3: Now, multiply the result obtained from step 2 by the remaining side of the main right triangle.

Step 4: The result obtained is called the altitude or the height of the right triangle.

For example, if the sides of a right triangle a, b, and c are 3 cm, 4 cm,  and 5 cm respectively, then the altitude on the hypotenuse is calculated as follows:

a = perpendicular side = 3 cm

b= base side = 4 cm

C = hypotenuse = 5 cm

Here, the smallest side of the right triangle is equal to 3 cm.

Therefore, divide the perpendicular side by the hypotenuse, we get

Altitude = ⅗ = 0.6

Now, multiply the result by the base side of the right triangle.

Altitude = 0.6 x 4

Altitude = 2.4 cm 

Therefore, the altitude on the hypotenuse of a right triangle is 2.4 cm.

Similarly, the altitude can be found using trigonometry. The angles on the smaller triangles are the same as the angles in the main right triangle. Thus, by using the trigonometry formulas, we can find the altitude.

Hypotenuse Examples

Let us solve some examples based on the hypotenuse concept.

If the base and perpendicular of a right-angled triangle are 3cm and 4cm, respectively, find the hypotenuse.

Given, base = 3cm and perpendicular = 4cm

By the hypotenuse formula, we know;

Hypotenuse = √(Base 2 + Perpendicular 2 )

= √(3 2 + 4 2 )

= √(9 + 16)

Hence, the length of the hypotenuse is 5cm.

For an isosceles right-angled triangle, the two smallest sides are equal to 10cm. Find the length of the longest side.

The two equal sides of the isosceles right triangle are the base and perpendicular.

The longest side is the hypotenuse. Hence, by using the formula, we get;

H = √(10 2 + 10 2 )

H = √(100 + 100)

H = 10√2 cm

Frequently Asked Questions on Hypotenuse

What is meant by hypotenuse.

In Maths, a hypotenuse is the longest side of a right triangle. In other words, the side opposite to the right angle is called the hypotenuse.

What is the formula to calculate the hypotenuse?

The formula to calculate the hypotenuse of a right triangle is: Hypotenuse = √[Base 2 + Perpendicular 2 ]

How to calculate the altitude of a right triangle?

The altitude of a right triangle can be determined using the following steps: Step 1: Divide the smallest side of the right triangle by the length of the hypotenuse. Step 2: Multiply the result obtained from step 2 with the remaining side of the right triangle. The result is the altitude or the height of a right triangle.

What is meant by the right triangle altitude theorem?

The right triangle altitude theorem or the Geometric theorem states that the altitude to the hypotenuse of the right triangle forms two congruent triangles which are similar to the original right triangle.

How to find the hypotenuse of a right triangle?

The length of the hypotenuse of a right triangle can be found with the help of the Pythagoras theorem. The theorem states that the square of the hypotenuse is equal to the sum of the square of the other two sides.

Put your understanding of this concept to test by answering a few MCQs. Click ‘Start Quiz’ to begin!

Select the correct answer and click on the “Finish” button Check your score and answers at the end of the quiz

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How to Write a Hypothesis

Last Updated: May 2, 2023 Fact Checked

This article was co-authored by Bess Ruff, MA . Bess Ruff is a Geography PhD student at Florida State University. She received her MA in Environmental Science and Management from the University of California, Santa Barbara in 2016. She has conducted survey work for marine spatial planning projects in the Caribbean and provided research support as a graduate fellow for the Sustainable Fisheries Group. There are 9 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 1,034,627 times.

A hypothesis is a description of a pattern in nature or an explanation about some real-world phenomenon that can be tested through observation and experimentation. The most common way a hypothesis is used in scientific research is as a tentative, testable, and falsifiable statement that explains some observed phenomenon in nature. [1] X Research source Many academic fields, from the physical sciences to the life sciences to the social sciences, use hypothesis testing as a means of testing ideas to learn about the world and advance scientific knowledge. Whether you are a beginning scholar or a beginning student taking a class in a science subject, understanding what hypotheses are and being able to generate hypotheses and predictions yourself is very important. These instructions will help get you started.

Preparing to Write a Hypothesis

• If you are writing a hypothesis for a school assignment, this step may be taken care of for you.

• Focus on academic and scholarly writing. You need to be certain that your information is unbiased, accurate, and comprehensive. Scholarly search databases such as Google Scholar and Web of Science can help you find relevant articles from reputable sources.
• You can find information in textbooks, at a library, and online. If you are in school, you can also ask for help from teachers, librarians, and your peers.

• For example, if you are interested in the effects of caffeine on the human body, but notice that nobody seems to have explored whether caffeine affects males differently than it does females, this could be something to formulate a hypothesis about. Or, if you are interested in organic farming, you might notice that no one has tested whether organic fertilizer results in different growth rates for plants than non-organic fertilizer.
• You can sometimes find holes in the existing literature by looking for statements like “it is unknown” in scientific papers or places where information is clearly missing. You might also find a claim in the literature that seems far-fetched, unlikely, or too good to be true, like that caffeine improves math skills. If the claim is testable, you could provide a great service to scientific knowledge by doing your own investigation. If you confirm the claim, the claim becomes even more credible. If you do not find support for the claim, you are helping with the necessary self-correcting aspect of science.
• Examining these types of questions provides an excellent way for you to set yourself apart by filling in important gaps in a field of study.

• Following the examples above, you might ask: "How does caffeine affect females as compared to males?" or "How does organic fertilizer affect plant growth compared to non-organic fertilizer?" The rest of your research will be aimed at answering these questions.

• Following the examples above, if you discover in the literature that there is a pattern that some other types of stimulants seem to affect females more than males, this could be a clue that the same pattern might be true for caffeine. Similarly, if you observe the pattern that organic fertilizer seems to be associated with smaller plants overall, you might explain this pattern with the hypothesis that plants exposed to organic fertilizer grow more slowly than plants exposed to non-organic fertilizer.

Formulating Your Hypothesis

• You can think of the independent variable as the one that is causing some kind of difference or effect to occur. In the examples, the independent variable would be biological sex, i.e. whether a person is male or female, and fertilizer type, i.e. whether the fertilizer is organic or non-organically-based.
• The dependent variable is what is affected by (i.e. "depends" on) the independent variable. In the examples above, the dependent variable would be the measured impact of caffeine or fertilizer.
• Your hypothesis should only suggest one relationship. Most importantly, it should only have one independent variable. If you have more than one, you won't be able to determine which one is actually the source of any effects you might observe.

• Don't worry too much at this point about being precise or detailed.
• In the examples above, one hypothesis would make a statement about whether a person's biological sex might impact the way the person is affected by caffeine; for example, at this point, your hypothesis might simply be: "a person's biological sex is related to how caffeine affects his or her heart rate." The other hypothesis would make a general statement about plant growth and fertilizer; for example your simple explanatory hypothesis might be "plants given different types of fertilizer are different sizes because they grow at different rates."

• Using our example, our non-directional hypotheses would be "there is a relationship between a person's biological sex and how much caffeine increases the person's heart rate," and "there is a relationship between fertilizer type and the speed at which plants grow."
• Directional predictions using the same example hypotheses above would be : "Females will experience a greater increase in heart rate after consuming caffeine than will males," and "plants fertilized with non-organic fertilizer will grow faster than those fertilized with organic fertilizer." Indeed, these predictions and the hypotheses that allow for them are very different kinds of statements. More on this distinction below.
• If the literature provides any basis for making a directional prediction, it is better to do so, because it provides more information. Especially in the physical sciences, non-directional predictions are often seen as inadequate.

• Where necessary, specify the population (i.e. the people or things) about which you hope to uncover new knowledge. For example, if you were only interested the effects of caffeine on elderly people, your prediction might read: "Females over the age of 65 will experience a greater increase in heart rate than will males of the same age." If you were interested only in how fertilizer affects tomato plants, your prediction might read: "Tomato plants treated with non-organic fertilizer will grow faster in the first three months than will tomato plants treated with organic fertilizer."

• For example, you would not want to make the hypothesis: "red is the prettiest color." This statement is an opinion and it cannot be tested with an experiment. However, proposing the generalizing hypothesis that red is the most popular color is testable with a simple random survey. If you do indeed confirm that red is the most popular color, your next step may be to ask: Why is red the most popular color? The answer you propose is your explanatory hypothesis .

• An easy way to get to the hypothesis for this method and prediction is to ask yourself why you think heart rates will increase if children are given caffeine. Your explanatory hypothesis in this case may be that caffeine is a stimulant. At this point, some scientists write a research hypothesis , a statement that includes the hypothesis, the experiment, and the prediction all in one statement.
• For example, If caffeine is a stimulant, and some children are given a drink with caffeine while others are given a drink without caffeine, then the heart rates of those children given a caffeinated drink will increase more than the heart rate of children given a non-caffeinated drink.

• Using the above example, if you were to test the effects of caffeine on the heart rates of children, evidence that your hypothesis is not true, sometimes called the null hypothesis , could occur if the heart rates of both the children given the caffeinated drink and the children given the non-caffeinated drink (called the placebo control) did not change, or lowered or raised with the same magnitude, if there was no difference between the two groups of children.
• It is important to note here that the null hypothesis actually becomes much more useful when researchers test the significance of their results with statistics. When statistics are used on the results of an experiment, a researcher is testing the idea of the null statistical hypothesis. For example, that there is no relationship between two variables or that there is no difference between two groups. [8] X Research source

Hypothesis Examples

Community Q&A

• Remember that science is not necessarily a linear process and can be approached in various ways. [10] X Research source Thanks Helpful 0 Not Helpful 0
• When examining the literature, look for research that is similar to what you want to do, and try to build on the findings of other researchers. But also look for claims that you think are suspicious, and test them yourself. Thanks Helpful 0 Not Helpful 0
• Be specific in your hypotheses, but not so specific that your hypothesis can't be applied to anything outside your specific experiment. You definitely want to be clear about the population about which you are interested in drawing conclusions, but nobody (except your roommates) will be interested in reading a paper with the prediction: "my three roommates will each be able to do a different amount of pushups." Thanks Helpful 0 Not Helpful 0

You Might Also Like

• ↑ https://undsci.berkeley.edu/for-educators/prepare-and-plan/correcting-misconceptions/#a4
• ↑ https://owl.purdue.edu/owl/general_writing/common_writing_assignments/research_papers/choosing_a_topic.html
• ↑ https://owl.purdue.edu/owl/subject_specific_writing/writing_in_the_social_sciences/writing_in_psychology_experimental_report_writing/experimental_reports_1.html
• ↑ https://www.grammarly.com/blog/how-to-write-a-hypothesis/
• ↑ https://grammar.yourdictionary.com/for-students-and-parents/how-create-hypothesis.html
• ↑ https://flexbooks.ck12.org/cbook/ck-12-middle-school-physical-science-flexbook-2.0/section/1.19/primary/lesson/hypothesis-ms-ps/
• ↑ https://iastate.pressbooks.pub/preparingtopublish/chapter/goal-1-contextualize-the-studys-methods/
• ↑ http://mathworld.wolfram.com/NullHypothesis.html
• ↑ http://undsci.berkeley.edu/article/scienceflowchart

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Before writing a hypothesis, think of what questions are still unanswered about a specific subject and make an educated guess about what the answer could be. Then, determine the variables in your question and write a simple statement about how they might be related. Try to focus on specific predictions and variables, such as age or segment of the population, to make your hypothesis easier to test. For tips on how to test your hypothesis, read on! Did this summary help you? Yes No

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Unit 12: Significance tests (hypothesis testing)

About this unit.

Significance tests give us a formal process for using sample data to evaluate the likelihood of some claim about a population value. Learn how to conduct significance tests and calculate p-values to see how likely a sample result is to occur by random chance. You'll also see how we use p-values to make conclusions about hypotheses.

The idea of significance tests

• Simple hypothesis testing (Opens a modal)
• Idea behind hypothesis testing (Opens a modal)
• Examples of null and alternative hypotheses (Opens a modal)
• P-values and significance tests (Opens a modal)
• Comparing P-values to different significance levels (Opens a modal)
• Estimating a P-value from a simulation (Opens a modal)
• Using P-values to make conclusions (Opens a modal)
• Simple hypothesis testing Get 3 of 4 questions to level up!
• Writing null and alternative hypotheses Get 3 of 4 questions to level up!
• Estimating P-values from simulations Get 3 of 4 questions to level up!

Error probabilities and power

• Introduction to Type I and Type II errors (Opens a modal)
• Type 1 errors (Opens a modal)
• Examples identifying Type I and Type II errors (Opens a modal)
• Introduction to power in significance tests (Opens a modal)
• Examples thinking about power in significance tests (Opens a modal)
• Consequences of errors and significance (Opens a modal)
• Type I vs Type II error Get 3 of 4 questions to level up!
• Error probabilities and power Get 3 of 4 questions to level up!

Tests about a population proportion

• Constructing hypotheses for a significance test about a proportion (Opens a modal)
• Conditions for a z test about a proportion (Opens a modal)
• Reference: Conditions for inference on a proportion (Opens a modal)
• Calculating a z statistic in a test about a proportion (Opens a modal)
• Calculating a P-value given a z statistic (Opens a modal)
• Making conclusions in a test about a proportion (Opens a modal)
• Writing hypotheses for a test about a proportion Get 3 of 4 questions to level up!
• Conditions for a z test about a proportion Get 3 of 4 questions to level up!
• Calculating the test statistic in a z test for a proportion Get 3 of 4 questions to level up!
• Calculating the P-value in a z test for a proportion Get 3 of 4 questions to level up!
• Making conclusions in a z test for a proportion Get 3 of 4 questions to level up!

Tests about a population mean

• Writing hypotheses for a significance test about a mean (Opens a modal)
• Conditions for a t test about a mean (Opens a modal)
• Reference: Conditions for inference on a mean (Opens a modal)
• When to use z or t statistics in significance tests (Opens a modal)
• Example calculating t statistic for a test about a mean (Opens a modal)
• Using TI calculator for P-value from t statistic (Opens a modal)
• Using a table to estimate P-value from t statistic (Opens a modal)
• Comparing P-value from t statistic to significance level (Opens a modal)
• Free response example: Significance test for a mean (Opens a modal)
• Writing hypotheses for a test about a mean Get 3 of 4 questions to level up!
• Conditions for a t test about a mean Get 3 of 4 questions to level up!
• Calculating the test statistic in a t test for a mean Get 3 of 4 questions to level up!
• Calculating the P-value in a t test for a mean Get 3 of 4 questions to level up!
• Making conclusions in a t test for a mean Get 3 of 4 questions to level up!

More significance testing videos

• Hypothesis testing and p-values (Opens a modal)
• One-tailed and two-tailed tests (Opens a modal)
• Z-statistics vs. T-statistics (Opens a modal)
• Small sample hypothesis test (Opens a modal)
• Large sample proportion hypothesis testing (Opens a modal)

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How to Write a Hypothesis for Correlation

How to Calculate a P-Value

A hypothesis is a testable statement about how something works in the natural world. While some hypotheses predict a causal relationship between two variables, other hypotheses predict a correlation between them. According to the Research Methods Knowledge Base, a correlation is a single number that describes the relationship between two variables. If you do not predict a causal relationship or cannot measure one objectively, state clearly in your hypothesis that you are merely predicting a correlation.

Research the topic in depth before forming a hypothesis. Without adequate knowledge about the subject matter, you will not be able to decide whether to write a hypothesis for correlation or causation. Read the findings of similar experiments before writing your own hypothesis.

Identify the independent variable and dependent variable. Your hypothesis will be concerned with what happens to the dependent variable when a change is made in the independent variable. In a correlation, the two variables undergo changes at the same time in a significant number of cases. However, this does not mean that the change in the independent variable causes the change in the dependent variable.

Construct an experiment to test your hypothesis. In a correlative experiment, you must be able to measure the exact relationship between two variables. This means you will need to find out how often a change occurs in both variables in terms of a specific percentage.

Establish the requirements of the experiment with regard to statistical significance. Instruct readers exactly how often the variables must correlate to reach a high enough level of statistical significance. This number will vary considerably depending on the field. In a highly technical scientific study, for instance, the variables may need to correlate 98 percent of the time; but in a sociological study, 90 percent correlation may suffice. Look at other studies in your particular field to determine the requirements for statistical significance.

State the null hypothesis. The null hypothesis gives an exact value that implies there is no correlation between the two variables. If the results show a percentage equal to or lower than the value of the null hypothesis, then the variables are not proven to correlate.

Record and summarize the results of your experiment. State whether or not the experiment met the minimum requirements of your hypothesis in terms of both percentage and significance.

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• University of New England; Steps in Hypothesis Testing for Correlation; 2000
• Research Methods Knowledge Base; Correlation; William M.K. Trochim; 2006
• Science Buddies; Hypothesis

About the Author

Brian Gabriel has been a writer and blogger since 2009, contributing to various online publications. He earned his Bachelor of Arts in history from Whitworth University.

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