Alternative Questions for Chapters 8-10

Question 1

What does it mean to reject the null hypothesis?

Answer 1

Implies that sample comes from a different population than null

Question 2

What does retaining a null hypothesis tell?

Answer 2

Did not find sufficient evidence to reject it

Question 3

What does retaining a null hypothesis not mean?

Answer 3

That null is true or even probably true

Question 4

How do make the standard error formula unbiased?

Answer 4

Sx(bar)= sx / sq rt of n

Question 5

What does estimating the standard deviation mean?

Answer 5

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

Question 6

What are the similarities between the z and t distributions?

Answer 6

Symmetrical, unimodal, mean of 0

Question 7

What are the differences between the z and t distributions?

Answer 7

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

Question 8

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

Answer 8

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

Question 9

What does the degree of freedom represent?

Answer 9

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

Question 10

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

Answer 10

N-1 degrees of freedom

Question 11

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

Answer 11

No

Question 12

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

Answer 12

Result is significant

Question 13

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

Answer 13

Likelihood of obtaining significant result is largely influence by sample size

Question 14

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

Answer 14

Importance depends heavily on research context in which results are evaluated

Question 15

What is another way to think about a sample mean?

Answer 15

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

Question 16

What happens when standard deviation is unknown?

Answer 16

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

Question 17

What are conclusions about hypothesis testing based on?

Answer 17

Probability not certainty

Question 18

What is possible with all hypothesis testing?

Answer 18

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

Question 19

Which error type is more serious and why?

Answer 19

Type 1

Question 20

What does changing the alpha do in a test?

Answer 20

Makes type 1 smaller while increasing type 2

Question 21

What is the alpha value?

Answer 21

Criterion for how unlikely the result must be to reject null

Question 22

What does the alpha value result mean?

Answer 22

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

Question 23

What does changing the sample size do in a test?

Answer 23

Less change of making a type 2 error

Question 24

What does changing the sample size in a test mean?

Answer 24

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

Question 25

What does changing the sample size mean?

Answer 25

affects error by altering standard error of mean

Question 26

What do bigger samples provide in a test?

Answer 26

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

Question 27

What is power the probability of?

Answer 27

Finding significant difference when you perform your hypothesis test

Question 28

What question are you asking yourself in post-hoc?

Answer 28

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?

Question 29

What does post-hoc mean?

Answer 29

After a hypothesis test is performed

Question 30

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

Answer 30

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

Question 31

what are the factors that influence type 1 error?

Answer 31

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

Question 32

What are the factors the influence a type 2 error?

Answer 32

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

Question 33

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

Answer 33

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

Question 34

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

Answer 34

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

Question 35

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

Answer 35

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

Question 36

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

Answer 36

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

Question 37

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

Answer 37

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).

Question 38

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

Answer 38

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

Question 39

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

Answer 39

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

Question 40

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

Answer 40

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

Question 41

What is the sampling distribution of independent samples test?

Answer 41

distribution of the differences between the means of two independent samples

Question 42

What is Hedge’s g?

Answer 42

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

Question 43

How do you calculate Hedge’s g?

Answer 43

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

Question 44

When is Hedge’s g particularly useful?

Answer 44

comparing the means of two groups

Question 45

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

Answer 45

independence of observations, normality, homogeneity of variance

Question 46

What is independence of observations?

Answer 46

observations in each sample must be independent of each other

Question 47

What is normality?

Answer 47

data in each sample should be approximately normally distributed

Question 48

What is homogeneity of variance?

Answer 48

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

Question 49

Why is homogeneity of variance important?

Answer 49

many statistical tests rely on it to give valid results

Question 50

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

Answer 50

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

Question 51

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…

Answer 51

Want to avoid making a type 2 error

Question 52

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?

Answer 52

Increase the chance of their concerns becoming real

Question 53

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

Answer 53

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