Chapter 9

Question 1

Inferential Statistics

Answer 1

Statistical procedures designed to determine if differences and relationships found in sample data are sufficiently large that they can be assumed to be true at the population level

Question 2

Degree of Uncertainty

Answer 2

All inferences from samples to populations involve a degree of uncertainty. The amount of uncertainty is determined by a number of factors, including sampling error and measurement error.

Question 3

Measurement Error

Answer 3

This is differences in estimates of a population parameter based upon different testings of the same sample using the same instrument. These differences are the result of unreliability in our measurement instrument.

Question 4

Sampling Error

Answer 4

This is the differences in estimates of a population parameter based upon different samples drawn from the same population. If the samples were randomly drawn and all of the same size, the amount of error (at a certain probability level) can be calculated.

Question 5

Null Hypothesis

Answer 5

There is no difference between the groups (or the difference is in the unpredicted direction)

Question 6

Alternative Hypothesis

Answer 6

There is a difference between the groups (or the difference is in the predicted direction)

Question 7

level of significance

Answer 7

also known as a level

Question 8

If the _____________ would have generated the sample statistic less often by chance than the a level, the researcher rejects the ______ and affirms the alternative.

Answer 8

null hypothesis, null

Question 9

Type I Error

Answer 9

Rejecting the null when it is in fact true

Question 10

Type II Error

Answer 10

Failing to reject the null when it is in fact false

Question 11

Difference between group means

Answer 11

larger differences make it easier to achieve significance, all other things being equal

Question 12

Sample size (N)

Answer 12

larger sample sizes reduce sampling error and make it easier to achieve significance, all other things being equal

Question 13

Reliability of the instruments

Answer 13

more reliable instruments reduce measurement error, and make it easier to achieve significance, all other things being equal

Question 14

Confidence Intervals

Answer 14

An interval within which we believe the true population parameter falls, at a given level of confidence (usually 95% or 99%)

Question 15

Effect Size

Answer 15

Statistical significance answers the question, “Are the results likely to be due to sampling error?”

Question 16

Sample size does not play a role in ______________.

Answer 16

effect size

Question 17

Cohen’s d =

Answer 17

Mean One – Mean Two/Standard Deviation (Either Pooled or for Control)

Question 18

Coefficient of Determination =

Answer 18

r squared (for correlations)

Question 19

Eta Squared =

Answer 19

Sum of Squared Deviations Between/Sum of Squared Deviations Total

Question 20

Parametric Statistics

Answer 20

Inferential statistical tests that make a number of assumptions about the data (normality, equality of group variances, and interval/ratio level of measurement)

Question 21

Non-Parametric Statistics

Answer 21

Inferential statistical tests that make relatively few assumption about the data

Question 22

Parametric statistics

Answer 22

are more “powerful” than non-parametric statistics; that is, they are more likely to reject the null hypothesis when it is in fact false

Question 23

The t-test

Answer 23

Tests for differences between the means of two groups.

Question 24

Independent samples t-test

Answer 24

Used to test differences in means of two different groups of subjects

Question 25

Paired dependent samples t-test

Answer 25

Used to test differences in means of two groups of subjects who are either the same or matched on one or more variables

Question 26

T-test for correlations

Answer 26

Tests whether a sample correlation is large enough to indicate a relationship different from zero in the population

Question 27

Simple Analysis of Variance (One-Way ANOVA)

Answer 27

Tests for differences in the means of three or more groups representing levels of a single IV factor

Question 28

Factorial Analysis of Variance (N-way ANOVA)

Answer 28

Allows testing of multiple IVs, each of which may have many levels. Allows determination of the significance of each IV Allows determination of the significance of changes in an IV as a function of changes in other IVs

Question 29

Univariate

Answer 29

techniques have a single DV

Question 30

Multivariate techniques

Answer 30

have multiple DVs | account for the correlations among the DVs (which would not happen if you ran multiple univariate tests)

Question 31

Chi-Square

Answer 31

Used to analyze relationships among categorical variables Appropriate when the DV is frequency of occurrence data (how many cases fall into each category or combination of categories)

Question 32

Chi-square

Answer 32

is a non-parametric statistical test

Question 33

Criteria for Evaluating Inferential Statistics

Answer 33

Basic descriptive statistics are needed to evaluate the results of inferential statistics Inferential analyses refer to statistical, not practical significance Inferential analyses do not indicate external validity (unless appropriate sampling was used in the design phase) Inferential analyses do not indicate internal validity The results of inferential tests depend on the number of subjects The appropriate statistical test should be used The level of significance should be interpreted correctly Be wary of statistical tests with small numbers of subjects in one or more groups or categories