| Statistic | Purpose | APA Style | Description |
|---|---|---|---|
| Descriptive Statistics | |||
| Mean | To provide an estimate of the population from which the sample was selected. | M = _____ | Indicates the center point of the distribution and serves as the reference point for nearly all other statistics. |
| Standard Deviation | To provide an estimate of the amount of variability/dispersion in the distribution of population scores. | SD = _____ | Indicates the variability of scores around their respective mean. Zero indicates no variability. |
| Measures of Effect Size | |||
| Cohen’s d | To provide a standardized measure of an effect (defined as the difference between two means). | d = _____. | Indicates the size of the treatment effect relative to the within-group variability of scores. |
| Correlation | To provide a measure of the association between two variables measured in a sample. | r(df) = _____ | Indicates the strength of the relationship between two variables. |
| Eta-Squared | To provide a standardized measure of an effect (defined as the relationship between two variables). | eta2 = _____. | Indicates the proportion of variance in the dependent variable accounted for by the independent variable. |
| Confidence Intervals | |||
| CI for a Mean | To provide an interval estimate of the population mean. | ____% CI [___, ___] | Estimates a range for the mean using a procedure that produces an accurate estimate the specified percentage of times. |
| CI for a Mean Difference | To provide an interval estimate of the population mean difference. | ____% CI [___, ___] | Estimates a range for the mean difference using a procedure that produces an accurate estimate the specified percentage of times. |
| Statistical Significance Tests | |||
| One Sample t Test | To compare a single sample mean to a population mean when the population standard deviation is not known | t(df) = ____, p = ____. | A small probability is obtained when the statistic is sufficiently large, indicating that the two means significantly differ from each other. |
| Independent Samples t Test | To compare two sample means when the samples are from a single-factor between-subjects design. | t(df) = ____, p = ____. | A small probability is obtained when the statistic is sufficiently large, indicating that the two means significantly differ from each other. |
| Paired Samples t Test | To compare two sample means when the samples are from a single-factor within-subjects design. | t(df) = ____, p = ____. | A small probability is obtained when the statistic is sufficiently large, indicating that the two means significantly differ from each other. |
| One-Way ANOVA | To compare two or more sample means when the means are from a single-factor between-subjects design. | F(df1,df2) = ___, p = ____. | A small probability is obtained when the statistic is sufficiently large, indicating that the set of means differ significantly from each other. |
| Repeated Measures ANOVA | To compare two or more sample means when the means are from a single-factor within-subjects design. | F(df1,df2) = ___, p = ____. | A small probability is obtained when the statistic is sufficiently large, indicating that the set of means differ significantly from each other. |
| Factorial ANOVA | To compare four or more groups defined by a multiple variables in a factorial research design. | F(df1,df2) = ___, p = ____. | A small probability is obtained when the statistic is sufficiently large, indicating that the set of means differ significantly from each other. |
Note. Many of the statistics from each of the categories are frequently and perhaps often appropriately presented in tables or figures rather than in the text.