APA Style | Summary of Statistics Reporting
In simple examples - such as those with single outcomes or single statistical tests - it is expected that researchers place statistical information in the text.
Descriptive Statistics
| Statistic |
Purpose |
APA Example |
| Mean |
To provide an estimate of the mean of the population from which the sample was selected. |
M = 4.00 |
| Standard Deviation |
To provide an estimate of the amount of variability/dispersion in the distribution of population scores. |
SD = 3.12 |
Measures of Effect Size
| Statistic |
Purpose |
APA Example |
| Cohen’s d |
To provide a measure of difference between two means relative to the within-group variability of scores. |
d = -.96 |
| Correlation |
To provide a measure of the size of the association between two variables measured in a sample. |
r(2) = .50 |
| Eta-Squared |
To provide the proportion of variance in a variable accounted for by another variable. |
η2 = .51 |
Confidence Intervals
| Statistic |
Purpose |
APA Example |
| CI for a Mean |
To provide an interval estimate of the population mean. |
95% CI [-5.61, -0.39] |
| CI for a Mean Difference |
To provide an interval estimate of the population mean difference. |
95% CI [-8.24, 0.24] |
Statistical Significance Tests
| Statistic |
Purpose |
APA Example |
| One Sample t Test |
To compare a single sample mean to a population mean when the population standard deviation is not known |
t(7) = -2.72, p = .030 |
| Paired Samples t Test |
To compare two sample means when the samples are from a single-factor within-subjects design. |
t(3) = -3.27, p = .047 |
| Independent Samples t Test |
To compare two sample means when the samples are from a single-factor between-subjects design. |
t(6) = -2.31, p = .060 |
| One-Way ANOVA |
To compare two or more sample means when the means are from a single-factor between-subjects design. |
F(2, 9) = 4.67, p = .041 |
| Repeated Measures ANOVA |
To compare two or more sample means when the means are from a single-factor within-subjects design. |
F(1, 3) = 10.67, p = .047 |
| Factorial ANOVA |
To compare four or more groups defined by a multiple variables in a factorial research design. |
F(1, 12) = 0.67, p = .430 |