Chapter 8 Part 2 Flashcards

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1
Q

What is effect size?

A

Quantifying size diff between two groups to judge the significance of the results

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2
Q

What is an issue with hypothesis testing?

A

Only using critical/p-values without considering effect size and its effect on results

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3
Q

What is more likely to produce a significant sample size?

A

Small absolute difference between two means > more likely to be statistically significant with large sample than small

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4
Q

What are two ways to explain the difference between the two groups being compared?

A

Absolute diff between group means, standardized diff btw n group means

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5
Q

What is absolute effect size?

A

Diff between means expressed in the distributions of measurements

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6
Q

When is absolute effect size useful?

A

When variables have intrinsic and well-understood meanings

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7
Q

What is a downside to absolute effect size?

A

comparing two raw scores w/o thinking of distribution spread

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8
Q

What is standardized effect size?

A

Diff between group means

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9
Q

When is standardized effect size useful?

A

measurements have no intrinsic meaning, different scales of measurement

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10
Q

What does the standardized effect size serve the basis for?

A

Comparing differences across studies, used extensively in post-hoc meta-analyses

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11
Q

What is the standardized effect size equation mean?

A

difference between means is divided by the standard deviation to yield the standardized mean difference between groups

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12
Q

What does the standardized mean difference provide?

A

common ground for comparison

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13
Q

Why does the standard deviation need to be included in the calculation?

A

To correct for differences in the spread

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14
Q

When Cohen’s d be used?

A

When comparing mean scores of two groups

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15
Q

What is cohen’s d simply?

A

Difference between the two group means divided by the average of their standard deviations

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16
Q

How is cohen’s d arranged by size?

A

.2 is small, .5 is medium, and a .8 is large

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17
Q

How is cohen’s d calculated?

A

nothing more than the difference between two group means divided by their pooled standard deviations

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18
Q

An effect size of zero would indicate __________.

A

No effect of IV

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19
Q

Cohen’s d is used to calculate a ____ effect size….

A

standardized

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20
Q

What is a Type 1 error?

A

Rejecting the null hypothesis when it is in fact true

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21
Q

What does the level of significance of a statistical test also set?

A

The maximum probability of making a Type 1 error

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22
Q

In the case of errors what does an alpha also determine?

A

Probability of making a type 1 error

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23
Q

What is a type 2 error?

A

probability of rejecting the null when It is in fact false

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24
Q

What is the relationship between the type 1 and the type 2?

A

As the probability of the type 2 increases the probability of a type 1 decreases

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25
Q

What is the type 2 inversely related to?

A

level of significance

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26
Q

What does the type 2 error depend on?

A

Population mean

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27
Q

What is the correct decision probability for a type 1?

A

1-a

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28
Q

What is the correct decision probability for a type 2?

A

1-b

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29
Q

What is the first error that can be made in hypothesis testing?

A

Null hypothesis is true but the decision based on the testing is the null should be rejected

30
Q

What is the second error that can be made in hypothesis testing?

A

Null is false but testing concluded is should be accepted

31
Q

What is the power?

A

Probability of making a correct decision and rejecting the null when it is in fact false (no making a type 2 error)

32
Q

What is the first thing that can affect power?

A

sample size

33
Q

What is the second thing that can affect power?

A

Larger the n the greater the power of the test

34
Q

What is the third thing that can affect power?

A

Significance level

35
Q

What is the fourth thing that can affect power?

A

Higher the value of a (Type 1), higher the power of the test,

36
Q

What is the fifth thing that can affect power relating to the fourth?

A

Increasing size of rejection region and decreasing size of non-rejection region

37
Q

What is the fifth thing that can affect power?

A

The true value of the parameter being tested

38
Q

What is the sixth thing that can affect power?

A

Greater the difference between the true value of a parameter and specified null, greater the power of the test

39
Q

What is an important use of power in hypothesis testing?

A

Ensure that the sample size being considered is large enough for the purpose of the test

40
Q

What happens if power is not used in hypothesis testing?

A

results will be inconclusive and effort/resources will have been wasted

41
Q

Other things being equal, what will increase the power of a hypothesis test?

A

Increasing sample size

42
Q

A researcher is planning a study and is considering various options for alpha. Selecting a larger alpha value will result in decreased ____

A

Beta

43
Q

What is step 1 in hypothesis testing?

A

State claim/identify hypotheses

44
Q

What is step 2 in ht?

A

Determine alpha

45
Q

What is step 3 in ht?

A

Determine test

46
Q

What is step 4 in ht?

A

Critical value of test

47
Q

What is step 5 in ht?

A

Calculate test stat

48
Q

What is step 6 in ht?

A

Compare test stat to critical value

49
Q

What is the p-value?

A

Determine probability of the value of the stat given null is true

50
Q

What is step 7 in ht?

A

Interpret decision

51
Q

What happens if you have a large enough sample?

A

ANY difference can be significant

52
Q

What is effect size?

A

Estimate of the degree to which the effect is present in the population

53
Q

What is effect size simply?

A

Difference between uhyp and u true

54
Q

What is u true?

A

Sample mean

55
Q

What is u hypothesis

A

Value when null is true

56
Q

What are the standard measures of effect size?

A

Cohen’s d, hedge’s g, and Pearson’s r

57
Q

When do you use cohen’s d?

A

When you know the standard deviation

58
Q

Why do type 1 errors occur?

A

Possible to draw non-representative sample at random from a population

59
Q

How to control a type 1 error?

A

Changing alpha will change type 1 error

60
Q

How to control a type 2 error?

A

Can’t directly control it but there are factors that influence it (a, sample size)

61
Q

What power value is considered adequate?

A

.80

62
Q

What are the four general factors that influence power?

A

Alpha, effect size, sample size, population variability

63
Q

What happens when you increase alpha?

A

Decreases beta (type 2)

64
Q

What happens with one tailed tests in the correct direction?

A

decrease beta

65
Q

What happens with one tailed tests in the correct direction?

A

They increase power (relation to alpha)

66
Q

What happens when you increase effect size?

A

You increase power

67
Q

What happens if you increase sample size/decrease variability?

A

Power increases (type 2 decreases)

68
Q

What happens if n value increases?

A

Standard error decreases, type 2 error shrinks

69
Q

What happens if sample standard deviation decreases?

A

Standard error decreases (type 2 error decreases)

70
Q

When do you want to estimate power?

A

Before you begin a study

71
Q

What can a power curve help with?

A

Determining sample size needed for sufficient power