Alternative Questions for Chapters 8-10 Flashcards

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1
Q

What does it mean to reject the null hypothesis?

A

Implies that sample comes from a different population than null

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2
Q

What does retaining a null hypothesis tell?

A

Did not find sufficient evidence to reject it

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3
Q

What does retaining a null hypothesis not mean?

A

That null is true or even probably true

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4
Q

How do make the standard error formula unbiased?

A

Sx(bar)= sx / sq rt of n

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5
Q

What does estimating the standard deviation mean?

A

No longer assume that the sampling distribution will have all characteristics of a normal distribution

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6
Q

What are the similarities between the z and t distributions?

A

Symmetrical, unimodal, mean of 0

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7
Q

What are the differences between the z and t distributions?

A

T-distribution is more flat, t has a larger standard deviation, t has larger critical values

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8
Q

What does it mean that the t distribution has a larger critical value?

A

Sample mean has to be farther away from null to reject it

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9
Q

What does the degree of freedom represent?

A

Number of scores in a distribution that are completely free to vary

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10
Q

What does a single means t-test mean in regard to degree of freedom?

A

N-1 degrees of freedom

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11
Q

Is the procedure for hypothesis testing different for z-tests than t-tests?

A

No

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12
Q

What do we call it when we reject null after conducting a hypothesis test?

A

Result is significant

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13
Q

What is reason number 1 why statistical significance does mean importance?

A

Likelihood of obtaining significant result is largely influence by sample size

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14
Q

What is reason number 2 why statistical significance does mean importance?

A

Importance depends heavily on research context in which results are evaluated

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15
Q

What is another way to think about a sample mean?

A

Determine distance from the hypothesized value in terms of standard deviation of pop rather than standard error of sampling distribution

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16
Q

What happens when standard deviation is unknown?

A

Substitute our unbiased estimate of the sd for Hedge’s G

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17
Q

What are conclusions about hypothesis testing based on?

A

Probability not certainty

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18
Q

What is possible with all hypothesis testing?

A

That you have a perfect hypothesis and still arrive at the wrong answer

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19
Q

Which error type is more serious and why?

A

Type 1

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20
Q

What does changing the alpha do in a test?

A

Makes type 1 smaller while increasing type 2

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21
Q

What is the alpha value?

A

Criterion for how unlikely the result must be to reject null

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22
Q

What does the alpha value result mean?

A

if null is true likelihood of getting value in rejection region and therefore making type 1 error is also that value

23
Q

What does changing the sample size do in a test?

A

Less change of making a type 2 error

24
Q

What does changing the sample size in a test mean?

A

If null is not true you have better chance of rejecting It as the sample size gets bigger

25
Q

What does changing the sample size mean?

A

affects error by altering standard error of mean

26
Q

What do bigger samples provide in a test?

A

provide better estimates of the population mean so sampling distributions have smaller standards errors than distributions of smaller samples

27
Q

What is power the probability of?

A

Finding significant difference when you perform your hypothesis test

28
Q

What question are you asking yourself in post-hoc?

A

Given the way in which I have conducted this test, what is the likelihood that I would have found a significant difference is actually there?

29
Q

What does post-hoc mean?

A

After a hypothesis test is performed

30
Q

What are the four ways we determine the power of a z-test?

A

Value predicted by null, standard error of the mean for your hypothesis test, true mean of pop, alpha of the test

31
Q

what are the factors that influence type 1 error?

A

significance level set for the hypothesis test, the sample size, and the effect size.

32
Q

What are the factors the influence a type 2 error?

A

significance level, the sample size, the effect size, and the variance of the population

33
Q

Under what circumstances do we use a z-test vs. a t-test?

A

Z-test: population parameters are known, sample size is large
T-test: population parameters are unknown, sample size is small

34
Q

What makes calculating a t-test difference from a z-test?

A

t-test takes into account the degree of uncertainty that comes from estimating the population standard deviation from a sample.

35
Q

How do you conduct a hypothesis test of a single means t-test?

A

state hypothesis, formulate an analysis plan, analyze sample data, interpret results

36
Q

How do you calculate the effect size of a t-test?

A

This is calculated as the difference between the two means (or the mean difference) divided by the pooled standard deviation

37
Q

How are null and alternative different from two sample tests (compared to single means)?

A

main difference lies in what you’re comparing: a single population mean to a specific value (single mean t-test) or the means of two populations to each other (two-sample t-test).

38
Q

In a single means t-test what does the null and alternative typically state?

A

population mean is equal to a specified value, while the alternative hypothesis states that the population mean is different from that value

39
Q

In a two sample t-test what does the null and alternative typically state?

A

null hypothesis is typically that the means of the two populations are equal, while the alternative hypothesis is that the means are not equal

40
Q

What could the alternative alternatively state in a two sample t-test?

A

one mean is greater than or less than the other, depending on the question of interest

41
Q

What is the sampling distribution of independent samples test?

A

distribution of the differences between the means of two independent samples

42
Q

What is Hedge’s g?

A

measure of effect size, measure of the magnitude of the difference that is not dependent on the sample size

43
Q

How do you calculate Hedge’s g?

A

calculated as the difference between the two means divided by the pooled standard deviation, but then multiplied by a correction factor

44
Q

When is Hedge’s g particularly useful?

A

comparing the means of two groups

45
Q

What are the statistical assumptions of independent samples t-tests?

A

independence of observations, normality, homogeneity of variance

46
Q

What is independence of observations?

A

observations in each sample must be independent of each other

47
Q

What is normality?

A

data in each sample should be approximately normally distributed

48
Q

What is homogeneity of variance?

A

variances of the populations from which different samples are drawn are equal, spread or dispersion of scores around the mean is the same for all groups being compared

49
Q

Why is homogeneity of variance important?

A

many statistical tests rely on it to give valid results

50
Q

How to integrate various inferential statistics to consider the meaning and implications of a results?

A

consider the context, look for consistency, consider practical significance, think about implications

51
Q

Researchers are testing the potential side effects of a new anti-depressive medication. They conduct a study in which half of the participants receive the experimental medication, while the other half receive a pre-existing medication. They want to make sure that they can detect any side effects that may exist. In other words…

A

Want to avoid making a type 2 error

52
Q

Given the researchers concerns in question 6, what impact would changing the alpha level of the study from .05 to .01 have for their study?

A

Increase the chance of their concerns becoming real

53
Q

When we have to estimate the population variance or standard deviation using a sample, we use the formula s^{2}=\frac{\sum \left ( X-\overline{X} \right )^{2}}{n-1} instead of s^{2}=\frac{\sum \left ( X-\overline{X} \right )^{2}}{n}. We do this because

A

The second formula is likely to underestimate the standard deviation of the population (it’s a biased estimate).