Statistics Exam 2

Front 1

paired t-test

Back 1

technique for determining if differences exist between two dependent-based means

Front 2

What does the one sample z-test and the one sample t-test determine?

Back 2

if our sample mean is significantly different from the population mean

Front 3

What type of test would be used when pairs of participants are matched on one or more characteristics and randomly placed in two different groups (e.g. experimental and control)

Back 3

paired t-test

Front 4

What type of test would be used when twin studies (or siblings) where one twin is in Group 1 and the other is in Group 2

Back 4

paired t-test

Front 5

What is the null hypothesis for the paired t-test?

Back 5

u1=u2 There is no significant difference in performance within the two conditions

Front 6

What does the r in the paired t-test formula mean?

Back 6

the correlation between the scores from the 2 dependent samples.

Front 7

What should the magnitude of the r be for the scores to be considered dependent (i.e. related)

Back 7

.4 or greater

Front 8

What is the criteria for rejecting the null hypothesis?

Back 8

p value is less than or equal to an alpha of .05

Front 9

When is the z-test used?

Back 9

when the sample data has a perfect normal distribution

Front 10

What does the one sample z-test and the one sample t-test determine?

Back 10

if the sample mean is significantly different from the population mean

Front 11

When could the z-test be used?

Back 11

when all sample data had perfect normal distributions

Front 12

t distribution

Back 12

series of approximations of the normal curve for different sample sizes

Front 13

independent t-test, two-sample t-test, Student's t-test

Back 13

comparing 2 sample means rather than a sample mean to a population mean

Front 14

What makes up the independent variable in a independent t-test?

Back 14

there is 1 IV with 2 levels: the 2 different groups that constitute you samples

Front 15

What are the assumptions of the independent t-test.

Back 15

randomness, normality, interval/ratio data, 2 independent groups, 10 or more participants per group, homogeneity of variance

Front 16

What independent t-test assumption do you not have to worry about if the group sizes are equal?

Back 16

homogeneity of variance

Front 17

What do you do if the group sizes are not equal in an independent t-test?

Back 17

test for the assumption of equal variance

Front 18

Levene's test

Back 18

used for testing for equal variance

Front 19

what do you do if the variances between the gruops are equal in an independent t-test?

Back 19

You can use a different formula for t that uses a "pooled" or average variance for the groups. This usually results in a lower error term and thus greater power.

Front 20

When is the effect size used?

Back 20

before a study to estimate sample size- based on an average effect size from the literature

Front 21

What does effect sizehelp estimage?

Back 21

the meaningfulness of your treatment

Front 22

What can you use to get a better picture of the magnitude of the difference between two means after the study?

Back 22

effect size

Front 23

How is the effect size most often used?

Back 23

to describe the difference between the mean of the experimental group and the control group

Front 24

omega squared

Back 24

another way of evaluating effectiveness of treatment

Front 25

When should omega squared be calculated?

Back 25

after a t-test if a significant difference is found

Front 26

What does omega squared indicate?

Back 26

the proportion of the variance in the dependent variable that is explained by the independent variable

Front 27

normal distribution

Back 27

scores on the dependent variable can be expressed as a standard score as a basis of comparison

Front 28

What is the most common standard score used with a normal distribution?

Back 28

z-score

Front 29

z-scores

Back 29

the standardized score used to produce a normal curve with mean=0 and s=1. It essentially represents a raw score expressed in standard deviation units. Can convert raw scores from a distribution into z-scores.

Front 30

What must be known before raw scores can be reported as z-scores?

Back 30

mean and standard deviation

Front 31

The equations for calculating what is used by most stats programs based on z scores?

Back 31

skewness