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Setting a Hypothesis

Dr. Shalini Sinha

Head of Department,

Department of Management Studies

NRI Institute of Information Science & Technology

Bhopal

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How to Write a Hypothesis

• Often, one of the trickiest parts of designing and writing up any research study is how to write a hypothesis.

• It is just about making sure that you are asking the right questions and wording your hypothesis statements correctly.

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The Three-Step Process

• Step one is to think of a general general hypothesishypothesis, including everything everything that you have observed and that you have observed and reviewed reviewed during the information information gathering stagegathering stage of any research design.

• This stage is often called developing developing the research problem.the research problem.

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Formulating a Hypothesis• You have a question and now you

need to turn it into a hypothesis.

• A hypothesis is an educated prediction that provides an explanation for an observed event.

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• An observed event is a measurable result or condition.

• If you can't measure it, then you can't form a hypothesis about it because you can't confirm or reject it.

• In addition, a hypothesis typically takes the form of an if-then statement so you can test it with your research.

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What does our hypothesis look like?

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Observation

Bright light has an adverse impact on

studying.

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hypothesis

• What does our hypothesis look like?

• 'If we increase the amount of light during studying, then the participant's performance on test scores will decrease.'

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Let's break down our hypothesis.• First off, it is an if-then statement:

• 'If we increase..., then the participant's...’

• This creates a prediction that we can test by increasing the light on participants as they study and then see if their test scores go down.

• It also means that the hypothesis can be proven correct or incorrect based on what happens to the test scores.

• If test scores don't change, then our hypothesis was incorrect and we will reject it.

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• You probably also noticed that we changed 'studying' to 'test scores' and the vague term about 'bright light' into 'amount of light.'

• This is an example of operationalizingoperationalizing, which is finding a way to measure or quantify a variable.

• Studying can't really be researched, but test scores can.

• And they are basically the same thing since studying typically increases test scores.

• Also, simply saying 'light' is too vague to be useful or researched, so it was turned into 'amount of light.

Research hypothesis

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Null Hypothesis• After you formulated your research

hypothesis, what if there isn't a connection between light and studying?

• That is kind of what a null hypothesis is;

• A null hypothesis is defined as a prediction that there will be no effect observed during the study.

• The reason researchers develop a null

hypothesis is to ensure that their research can be proven false.

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Null Hypothesis• So whenever you are conducting a research with a

hypothesis, you will create a null hypothesis.

• Research typically includes a hypothesis, and

• when this is the case you will form a null hypothesis as a

counterbalancecounterbalance to ensure there is a way to to disprove your prediction.disprove your prediction.

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Null Hypothesis• Every hypothesis test contains a set of two a set of two

opposing statementsopposing statements, or hypotheseshypotheses, about a population parameterpopulation parameter.

• The first hypothesis is called the null null hypothesis,hypothesis, denoted HH00. .

• The null hypothesis always states that the population parameter is population parameter is equalequal  to the to the claimed value. claimed value.

• FOR EGFOR EG. -GROWTH OF INDUSTRIAL OUTPUT . -GROWTH OF INDUSTRIAL OUTPUT BEFORE &AFTER ECONOMIC REFORMS IS THE BEFORE &AFTER ECONOMIC REFORMS IS THE SAME. ( SAME. ( NO CHANGE DUE TO REFORMS.NO CHANGE DUE TO REFORMS.) ) BOTH BOTH ARE EQUALARE EQUAL..

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• For example, if the claim is that the average time to make a name-brand,MAGGI, ready-mix noodles is two minutes, the statistical shorthand notation for the null hypothesis in this case would be as follows:

Ho : µ = 2

• (That is, the population mean is 2 minutes.)

• All null hypotheses include an equal sign in them.

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Alternative Hypothesis• How to define an alternative hypothesis ?

• Before actually conducting a hypothesis test, you have to put two possible hypotheses on the table — the null hypothesis is one of them.

• But, if the null hypothesis is rejected (that is, there was sufficient evidence against it), what’s your alternative going to be?

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Alternative hypothesis• Actually, three possibilities exist for the

second (or alternative) hypothesis, denoted Ha. Here they are, along with their shorthand notations in the context of the Maggi noodles example:

1.1.The population parameter is The population parameter is not equalnot equal to the  to the

claimed value.claimed value. Ha : µ ≠ 2

2.2.The population parameter is The population parameter is greater thangreater than  the the

claimed value. claimed value. Ha : µ ≥ 2

3.3.The population parameter is The population parameter is less thanless than  the the

claimed value.claimed value. Ha : µ ≤ 2

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Alternative hypothesis

• Which alternative hypothesis you choose in setting up your hypothesis test depends on what you’re interested in concluding, should you have enough evidence to refute the null hypothesis (the claim).

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• The alternative hypothesis should be decided upon before collecting or looking at any data, so as not to influence the results.

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Alternative hypothesis

• For example, if you want to test whether a company is correct in claiming its noodles takes TWO minutes to make and it doesn’t matter whether the actual average time is more or less than that, you , you use the not-equal-to alternativeuse the not-equal-to alternative.

• Your hypotheses for that test would be:

Ha : µ ≠2

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Alternative hypothesis

• If you only want to see whether the time turns out to be greater than what the company claims (that is, whether the company is falsely advertising its quick prep time), you use the greater-than alternative, and your two hypotheses are

Ha : µ ≥ 2

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Alternative hypothesis

• Finally, say you work for the company marketing the NOODLES, and you think the NOODLES can be made in less than five minutes (and could be marketed by the company as such). The less-than alternative is the one you want, and your two hypotheses would be

Ha : µ ≤5

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Alternative hypothesis

• How do you know which hypothesis to put in H0 and which one to put in Ha?

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H0 

• Typically, the null hypothesis says that nothing new is happening;

• the previous result is the same now as it was before,

• or the groups have the same average (their difference is equal to zero).

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• In general, you assume that people’s claims are true until proven otherwise.

• So the question becomes: Can you prove otherwise?

• In other words, can you show sufficient evidence to reject H0?

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Another Example of How to Write a Hypothesis

• A worker on a fish-farm notices that his trout seem to have more Anchor worms  in the summer, when the water levels are low, and wants to find out why.

• His research leads him to believe that the amount of oxygen is the reason - fish that are oxygen stressed tend to be more susceptible to disease and parasites.

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• He proposes a general hypothesis.

• “Water levels affect the amount of Anchor worms  suffered by rainbow trout.”

• This is a good general hypothesis, but it gives no guide to how to design the research.

• The hypothesis must be refined to hypothesis must be refined to give a little directiongive a little direction..

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• “Rainbow trout suffer more worms when water levels are low.”

• Now there is some directionality,• but the hypothesis is not

really testable, s• o the final stage is to design an

experiment around which research can be designed, a testable hypothesis.

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• Rainbow trout suffer more worms in low water conditions because there is less oxygen in the water.”

• This is a testable hypothesis - he has established variablesestablished variables, and by measuring the amount of oxygen amount of oxygen in the water.

• He can see if there is a correlation against the number of number of worms worms on the fish.

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• This is an example of how a a gradual focusing of research gradual focusing of research helps to define how to write a hypothesis.

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• The null hypothesis is essentially the "devil's advocate" position.

• That is, it assumes that whatever you are trying to prove did not happen (hint: it usually states that something equals zero). For example, the two different teaching methods did not result in different exam performances (i.e., zero difference).

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• Another example might be that there is no relationship there is no relationship between anxiety and athletic between anxiety and athletic performance (i.e., the slope is performance (i.e., the slope is zero). zero).

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Alternative hypothesis

• The alternative hypothesis states the opposite of Ho and is usually the hypothesis you are trying to prove

• (e.g., the two different teaching methods did result in different exam performances).

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• Initially, you can state these hypotheses in more general terms (e.g., using terms like "effect", "relationship", etc.), as shown below for the teaching methods example:

• Null Hypothesis (H0):Undertaking seminar classes has no effect on students' performance.

• Alternative Hypothesis (HA):Undertaking seminar class has a positive effect on students' performance.

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The Next Stage - What to Do With the Hypothesis

• Once you have your hypothesis

• the next stage is to design the research,

• allowing a statistical analysis of data, and allowing you to test your hypothesis.

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• The statistical analysis will allow you to reject either the null or the alternative hypothesis.

• If the alternative is rejected, then you need to go back and refine the initial hypothesis or design a completely new research program.

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A rule of the thumb

• A rule of the thumb is to set the Null-Hypothesis to the outcome you do not want to be true i.e. the outcome whose direct opposite you want to show.

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• Basic example: Suppose you have developed a new medical treatment and you want to show that it is indeed better than placebo.

• Placebo.• a medicine or procedure prescribed for the

psychological benefit to the patient rather than for any physiological effect.

• a substance that has no therapeutic effect, used as a control in testing new drugs

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• So you set Null-Hypothesis H0:=new treament is equal or worse than placebo and Alternative Hypothesis H1:=new treatment is better than placebo.

• This because in the course of a statistical test you either reject the Null-Hypothesis (and favor the Alternative Hypothesis) or you cannot reject it.

• Since your "goal" is to reject the Null-Hypothesis you set it to the outcome you do not want to be true.

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• THANKS !