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Statistical Methods > L1 Experimental Design and Hypothesis Testing > Flashcards

L1 Experimental Design and Hypothesis Testing Flashcards

1
Q

How many are the steps in designing experiments?

A

Four

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2
Q

What are they?

A
  1. Formulate research questions or hypotheses.
  2. Translate the research hypotheses into a set of treatment conditions.
  3. Select an appropriate experimental design to test the different treatment conditions.
  4. Record the response measure that you are interested in.
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3
Q

What is independent variables (IV)?

A

Experimental or treatment variable. Test the IV

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4
Q

What is dependent variable (DV)?

A

The measured or response variable. Measure the DV.

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5
Q

What are the various types of IV?

A
  1. Quantitative Variables
  2. Qualitative Variables
  3. Classification Variables
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6
Q

What is quantitative variables?

A

Represents of variations in terms of amounts.

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7
Q

What is an example of quantitative variables?

A

Amount of drug.

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8
Q

What is qualitative variables?

A

Represents of variations in terms of kind or type.

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9
Q

What is an example of quantitative variables?

A

Strategy.

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10
Q

What is classification variables?

A

Represent variations that are intrinsic to the subjects of the experiment.

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11
Q

What are the examples of classification variables?

A

IQ, age and gender.

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12
Q

What is nuisance variables?

A

IV which, if left uncontrolled, could exert a systematic influence on the different treatment conditions.

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13
Q

What are examples of nuisance variables?

A

Temperature, time of the day and nature of participants.

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14
Q

What is a systematic influence?

A

One that affects your measured response variable, DV.

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15
Q

If nuisance variable is not controlled, what it will become?

A

Confounding variable.

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16
Q

What is one of the way to overcome nuisance variable, if it can’t be controlled?

A

Completely randomized design.

17
Q

What is completely randomized design?

A

Participants are randomly assigned to serve in one of the treatment conditions.

18
Q

What is another name for completely randomized design?

A

Between-groups design.

19
Q

What is randomized block design?

A

Treat a participant (subject) as a block, where the individual serves in all treatment conditions of an IV.

20
Q

What is another name for randomized block design?

A

Repeated-measures design or within-participants/within-subjects design.

21
Q

What is research hypothesis?

A

A general experimental statement about the assumed nature of the world. Broad statement tying together an IV to a DV.

22
Q

What is a statistical hypothesis?

A

A set of precise hypotheses about the parameters of the different treatment conditions.

23
Q

What are the two statistical hypotheses?

A

Null hypothesis, H0 and alternative hypothesis H1.

24
Q

What is the relationship between the two statistical hypotheses?

A

Mutually exclusive.

25
Q

What is the null hypothesis?

A

The hypothesis that is tested, typically gives the same value to the different populations: H0: μ1 = μ2 = μ3 = etc. No treatment effects in the population.

26
Q

What is the alternative hypothesis?

A

States that the values of the parameter in the different treatment populations are not all equal. H1: not all μs are equal.

27
Q

What are the principles in hypothesis testing?

A
  1. You cannot prove anything.
  2. You are always testing the null hypothesis.
  3. You are always trying to find evidence against null hypothesis: reject H0 to accept H1.
28
Q

What is sample means?

A

The sample mean from a group of observations is an estimate of the population mean.

29
Q

What is the criteria for rejecting the null hypothesis?

A

The significance level and represented by α (alpha), typically used is 0.05.

30
Q

What are the two types of errors in hypothesis testing?

A

Type I error and Type II error.

31
Q

What is Type I error also known as?

A

False positive.

32
Q

What is Type I error?

A

Reject the null hypothesis and accept the alternative hypothesis when the null hypothesis shouldn’t be rejected.

33
Q

What is the error in committing Type I error?

A

The error comes from being too liberal in rejecting H0.

34
Q

What is Type II error also known as?

A

False negative.

35
Q

What is Type II error?

A

Fail to reject the null hypothesis and accept it when the null hypothesis should have been rejected and the alternative hypothesis is true.

36
Q

What is the error in committing Type II error?

A

The error comes from being too conservative in rejecting H0.

Statistical Methods (1 decks)

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