Chapter 12: Descriptive Statistics*

Question 1

Descriptive statistics

Answer 1

statistics that describe and summarize the data collected, which includes measures of central tendency, variability, and covariation

Question 2

Effect-size

Answer 2

the magnitude of an effect observed, either to the extent to which 2 variables are associated or the size of the difference in scores between groups

Question 3

Cohen’s d

Answer 3

an effect size estimate that is the standardized mean difference in scores between two groups (expressed in units of standard deviations)

Question 4

Correlation coefficient

Answer 4

a statistic that describes how strongly two variables are related to one another or the degree to which they covary

Question 5

When is pearson r used?

Answer 5

when both variables have interval or ratio-scale properties (i.e. continuous variables); when detecting linear relationships, NOT curvilinear (will be r=0 but may have a non-linear relationship)

Question 6

Restriction of range

Answer 6

when only a subset of a variable’s possible values are sampled or observed, which can lead to misleading null or attenuated correlations

Question 7

Regression equation

Answer 7

Y= a + bX; an equation that represents a line drawn to best fit a set of data points, allowing one to predict values of one variable based on another variable

Question 8

Criterion variable

Answer 8

outcome variable that is being predicted in a regression analysis

Question 9

Predictor variable

Answer 9

variable used to predict changes in the criterion (or outcome) variable in regression analysis

Question 10

Multiple correlation (R)

Answer 10

a correlation between a combined set of predictor variables and one criterion variable

Question 11

Multiple regression

Answer 11

extension of the correlation technique that models the extent to which 1 or more predictor variables are related to one criterion variable

Question 12

Frequency distribution

Answer 12

a representation of how often each score was observed, arranged from lowest to highest score

Question 13

Outliers

Answer 13

scores that are very different from the rest of the scores in the dataset, also known as extreme scores; larger effect on small sample sizes

Question 14

Bar graph

Answer 14

a graph using bars to depict frequencies of responses, percentages, or means in 2 or more groups

Question 15

Pie chart

Answer 15

a circular graph in which frequencies or percentages are represented as slices of a pie

Question 16

Histogram

Answer 16

type of bar graph used when the variable on the x-axis is continuous, with each bar touching adjacent bars

Question 17

Mean or arithmetic average

Answer 17

obtained by summing scores then dividing this sum by the number of scores; for interval and ratio scale data; not outlier robust

Question 18

Normal distribution

Answer 18

distribution of scores for continuous variables, in which majority of the scores cluster around the mean, with fewer scores as they fall further from the mean

Question 19

Standard deviation (s)

Answer 19

average deviation of scores from the mean; square root of the variance

Question 20

Frequency polygons

Answer 20

graphs of frequencies for continuous variables, in which the frequency of each score is plotted on the vertical axis and these points are connected by straight lines

Question 21

Central tendency

Answer 21

a single number or value that attempts to summarize all of the data, describing the typical score or where most of the scores fall

Question 22

Median

Answer 22

a measure of central tendency defined as the middle score in a distribution that divides the distribution in half (or an average of 2 middle scores); calculated for continuous and ordinal variables; outlier robust

Question 23

Mode

Answer 23

a measure of central tendency defined as the most frequent score in a distribution of scores; calculated for variables in an interval, ratio, ordinal, or nominal scale

Question 24

Variability

Answer 24

the amount of dispersion for scores (for continuous variables) around some central value

Question 25

Variance (s^2)

Answer 25

a measure of the variability of scores about a mean; sum of squared deviations around mean divided by N-1; higher variance = greater variability

Question 26

Range

Answer 26

Max score - min score

Question 27

Why use Cohen’s d?

Answer 27

allows us to make direct comparisons when groups have different units of measurement

Question 28

Coefficient of determination (r^2)

Answer 28

squared correlation coefficient; a measure of shared variance i.e. proportion of variability in y accounted for/predicted by variability in x; 0 if no overlap and 1 if complete overlap

Question 29

Partial correlation

Answer 29

if adding a third variable changes the correlation coefficient, then the third variable partially explains the relationship between the original two variables

Question 30

Regression models

Answer 30

a set of theoretically relevant predictors predicting a criterion variable; can look at how 1 or more predictors uniquely predict variability in criterion

Question 31

What is the most important benefit of regression?

Answer 31

can investigate the role of multiple predictors in independently predicting the criterion