Analysis of variance (ANOVA): An inferential statistic that allows one to compare two or more means.
Coefficient of correlation: A number that represents the direction and strength of a correlation.
Coefficient of determination: The percentage of variation accounted for in one variable by knowing the value of another variable.
Correlational statistics: Statistics that determine the strength and direction of the relationship between two variables.
Criterion: The variable considered the dependent variable in a correlational study that is not a true experiment.
Critical value: The value to which an observed statistic is compared to determine statistical significance.
Dependent variable: The variable assessed by the experimenter to determine whether there is a difference due to the independent variable.
Descriptive statistics: Statistics that summarize research data.
Frequency distribution: A list of the frequency of each value or group of values in a set of scores.
Frequency histogram: A graph that displays the frequency of scores as bars.
Frequency polygon: A graph that displays the frequency of scores by connecting points representing them above each score.
Independent variable: Typically a variable of interest that the experimenter manipulates.
Inferential statistics: Statistics used to determine whether the changes observed in a sample are likely to be true of the population which the sample is intended to represent.
Line graph: A graph used to plot data showing the relationship between independent and dependent variables in an experiment.
Mean: The arithmetic average of a set of scores.
Median: The middlemost score in a set of scores that have been ordered from lowest to highest.
Mode: The score or category that occurs most frequently in a set of scores.
Negative skew: A graph that has scores bunching up toward the positive end of the abscissa.
Normal curve (distribution): A bell-shaped graph representing a hypothetical frequency distribution for a given characteristic in which most of the scores are clustered around the mean. The scores become less frequent the farther they appear above or below the mean.
Pearson’s product-moment correlation: Perhaps the most commonly used correlational statistic.
Percentile: The score at or below which a particular percentage of scores fall.
Pie graph: A graph that represents data as percentages of a pie.
Positive skew: A graph that has scores bunching up toward the negative end of the abscissa.
Power: The sensitivity of a study to allow the rejection of a false null hypothesis.
Predictor: The variable considered the independent variable in a study that is not a true experiment.
Range: A statistic representing the difference between the highest and lowest scores in a set of scores.
Scatter plot: A graph of a correlational relationship.
Standard deviation: A statistic representing the degree of dispersion of a set of scores around their mean.
Statistical significance: A low probability (usually less than 5 percent) that the results of a research study are due to chance factors rather than to the independent variable.
Statistics: Mathematical techniques used to summarize research data or to determine whether the data support the researcher’s hypothesis.
T-test: An inferential statistic that allows one to compare two means resulting from either a between-subjects design (the independent samples t-test) or a within-subjects design (the paired, matched, or dependent samples t-test).
Type I error: In hypothesis testing, rejecting a true null hypothesis that should be retained.
Type II error: In hypothesis testing, retaining a false null hypothesis that should be rejected.
Variance: A measure of variability indicating the average of the squared deviations from the mean.