Chapter 12

Question 1

Descriptive statistics

Answer 1

used to describe the characteristics of a sample or a population

Question 2

Inferential statistics

Answer 2

used to infer (that is, to estimate) population parameters (the value within the population) from a subgroup (a sample) of the population (recall that the value from the sample is referred to as a sample statistic)

Question 3

Univariate statistics

Answer 3

used when we are considering one variable

Question 4

bivariate statistics

Answer 4

used when considering two variables,

Question 5

multivariate statistics

Answer 5

examining three or more variables.

Question 6

Parametric statistics

Answer 6

built-in assumptions about the data distribution that must be met if the statistic is to be used

Question 7

non-parametric statistics

Answer 7

do not have built-in assumptions about the data distribution that must be met if the statistic is to be used

Question 8

frequency distribution reports

Answer 8

how many cases take on each value of the variable

Question 9

raw frequency

Answer 9

actual number of cases

Question 10

relative frequency

Answer 10

expressed as a percentage of the cases

Question 11

cumulative frequency

Answer 11

the running tally of cases that take on the current and all preceding values of the variable

Question 12

Measures of dispersion

Answer 12

a group of statistics that indicate how well the measure of central tendency represents the distribution,

Question 13

mode

Answer 13

the most frequently occurring value in the distribution

Question 14

variation ratio

Answer 14

the proportion of cases that do not fit within the modal category. variation ratio = 1 – (number of cases in modal category/number of total cases

Question 15

median

Answer 15

the “middle”; it is the value of the observation that splits the distribution of cases in half

Question 16

range

Answer 16

is the measure of dispersion used with ordinal-level variables. As the name implies, it is literally the range of possible values that the variable encompasses

Question 17

outlier

Answer 17

a case that differs significantly from the others

Question 18

mean

Answer 18

calculated by adding all values in a distribution and dividing by the total number of cases

Question 19

skew the mean

Answer 19

pulling it in the direction of the extreme scores

Question 20

standard deviation (S)

Answer 20

estimates the average amount that each observation differs from the mean.

Question 21

standardized scores (also known as z-scores)

Answer 21

scores expressed as the number of standard deviations they fall from the mean of the total distribution of scores

Question 22

contingency tables (also referred to as cross-tabulation tables or cross-tabs)

Answer 22

In these tables, the cell in which any individual case is located is contingent upon its scores for each of the variables.

Question 23

scatter plots

Answer 23

graphs in which the point where an individual case lies is contingent upon its scores for each of the variables.

Question 24

perfect correlation

Answer 24

exists when knowing the value on one variable always allows us to perfectly predict the value on the other.

Question 25

Measures of association.

Answer 25

indicate the strength of the relationship with a single numerical value.

Question 26

proportional reduction in error (PRE) measures.

Answer 26

A PRE measure is basically a before-and-after comparison: we compare the amount of error we have before knowing the value on the independent variable with the amount of remaining error after knowledge about the independent variable is taken into account. In other words, to what degree does knowledge about the independent variable reduce our error in predicting values of the dependent variable?

Question 27

the regression line

Answer 27

the line that best fits the data

Question 28

Analysis of variance (ANOVA)

Answer 28

a statistical technique in which the observed variance is partitioned into components (within-group and between-group variances); in political science, often used when the dependent variable is measured at the nominal or ordinal level (particularly the former) and the independent variables are measured at the interval level.

Question 29

Measures of variation:

Answer 29

statistical measures for the dispersion of scores around the central tendency.