research: statistics

Question 1

frequency distribution

Answer 1

Tabulation of the number of observations (or number of participants) per distinct response for a particular variable. It is presented in table format, rows indicating each distinct response and columns presenting the frequency for which that response occurred

Question 2

frequency polygon

Answer 2

A line graph of the frequency distribution that is used to visually display data that are ordinal, interval, or ratio. The X-axis typically indicates the possible values, and the Y-axis typically represents the frequency count for each of those values.

Question 3

histogram

Answer 3

A graph of connecting bars that shows the frequency of scores for a variable. Taller bars indicate greater frequency or number of responses. Histograms are used with quantitative and continuous variables (ordinal, interval, or ratio).

Question 4

bar graph

Answer 4

A graph that displays nominal data. Each bar represents a distinct (noncontinuous) response, and the height of the bar indicates the frequency of that response.

Question 5

central tendency

Answer 5

Measures of the typical or middle value of the data set. Measures of central tendency include the mean, median, and mode

Question 6

Variability

Answer 6

A measure of the spread in a distribution of scores or data points. The more dispersed the data points, the more variability a distribution has. The three main indicators of variability are range, standard deviation, and variance.

Question 7

interquartile range

Answer 7

The distance between the 75th percentile and the 25th percentile (i.e., the range of the middle 50% of the data). The interquartile range may be a more accurate estimate of variability when dealing with outliers or extreme values, as it eliminates the top and bottom quartiles

Question 8

standard deviation

Answer 8

The most frequently reported indicator of variability for interval or ratio data.

Question 9

sum of squares (SS)

Answer 9

The sum of the squared deviation scores, computed by subtracting the mean from each data point (deviation scores), squaring each deviation score, and adding them together.

Question 10

variance

Answer 10

A type of variability equal to the standard deviation squared

Question 11

Skewness

Answer 11

An asymmetrical distribution in which the data points do not cluster systematically around a mean. Distributions can be positively skewed, with a greater number of data points clustering around the lower end, or negatively skewed, with a greater number of data points clustering around the higher end of the distribution.

Question 12

Kurtosis

Answer 12

The degree of peakedness of a distribution. Distributions can be mesokurtic (normal curve), leptokurtic (tall and thin), and platykurtic (flat and wide).

Question 13

Inferential Statistics

Answer 13

Statistical procedures that are used to draw inferences about a population from a sample.

Question 14

degrees of freedom

Answer 14

An important concept used in inferential statistics, that refers to the number of independent variables (IVs) “free to vary.” Computing df depends on the statistical test used.

Question 15

Correlation coefficient

Answer 15

A numerical index that represents the relationship between two variables. Index values range from .00 to 1.00 in both the positive and negative directions, with +1.00 indicating a perfect positive relationship and a -1.00 indicating a perfect negative relationship. Four commonly used types of correlation coefficients include (a) Pearson product moment correlation coefficient (commonly referred to as Pearson r), (b) Spearman r (for comparing rank-order variables), (c) biserial correlation coefficients (comparing one continuous and one dichotomous or dummy coded variable), and (d) point biserial correlation coefficients (relating one continuous and one true dichotomous variable). A correlation provides information about the relationship between two variables, including whether there is a relationship at all, the direction of that relationship, and the strength of the relationship.

Question 16

spurious correlation

Answer 16

Occurs when a correlation overrepresents or underrepresents the actual relationship.

Question 17

attenuation

Answer 17

A misleading correlation that occurs when unreliable measures indicate a lower relationship between two variables than actually exists

Question 18

Regression studies

Answer 18

Used to predict outcomes (dependent variable) from a predictor variable(s) (independent variable). The three types of regression are (a) bivariate regression (how well scores from an independent variable (predictor variable) predict scores on the dependent variable (criterion variable]), (b) multiple regression involves more than one predictor variable when each predictor variable is weighted [beta weights) in a regression equation to determine the contribution of each variable to the criterion variable), and (c) logistic regression (used when the dependent variable is dichotomous; may be similar to a bivariate or multiple regression).

Question 19

Nonparametric Statistics

Answer 19

Statistical tests that are used when researchers are only able to make a few assumptions about the distribution of scores in the underlying population. Specifically, their use is suggested when nominal or ordinal data are involved or when interval or ratio data are not distributed normally (i.e., are skewed).

Question 20

chi-square test

Answer 20

A nonparametric statistical test used to determine whether two or more categorical or nominal variables are statistically independent.

Question 21

Mann-Whitney U test

Answer 21

A nonparametric statistical test that compares two groups on a variable that is ordinally scaled. This test is analogous to a parametric independent t-test.

Question 22

Kolmogorov-Smirnov Z procedure

Answer 22

A nonparametric statistical test similar to the Mann-Whitney U test but more appropriate to use when samples are smaller than 25 participants.

Question 23

Kruskal-Wallis test

Answer 23

: A nonparametric statistical test analogous to an ANOVA and used when there are three or more groups per independent variable as well as an ordinal-scaled dependent variable.

Question 24

Wilcoxon’s signed-ranks test

Answer 24

A nonparametric statistical test equivalent to a dependent t-test; involves ranking the amount and direction of change for each pair of scores

Question 25

Friedman’s rank test

Answer 25

A nonparametric statistical test similar to Wilcoxon’s signed-ranks test in that it is designed for repeated measures. It may be used with more than two comparison groups

Question 26

Factor Analysis

Answer 26

A statistical test used to reduce a larger number of variables (often items on an assessment) to a smaller number of factors (groups or factors). The two forms of factor analysis are (a) exploratory factor analysis (EFA), which involves an initial examination of potential models (or factor structures) that best categorize the variables and (b) confirmatory factor analysis (CFA), which refers to confirming the EFA results.

Question 27

Meta-Analysis

Answer 27

: Involves statistically comparing the results across several similar studies for particular outcome or dependent variables

Question 28

effect size

Answer 28

A measure of the strength of the relationship between two variables in a population.