The table of descriptive statistics can be used to determine the inferential statistics.
Summary Statistics for the Data
N M SD Skew Kurt
Outcome1 4.000 2.000 2.449 0.544 -2.944
Outcome2 4.000 6.000 2.449 0.544 -2.944
The descriptive statistics are calculated separately for each instance (which are shown as separate variables).
The tables of inferential statistics show the key elements to be calculated.
Confidence Interval for the Mean Difference
Diff SE df LL UL
Comparison 4.000 1.225 3.000 0.102 7.898
Hypothesis Test for the Mean Difference
Diff SE df t p
Comparison 4.000 1.225 3.000 3.266 0.047
Confidence Interval for the Standardized Mean Difference
d SE LL UL
Comparison 1.633 0.782 0.101 3.165
Here, t = 3.266 and p = .047. This would be considered a statistically significant finding.
Using “CI for Mean Difference”, the researcher estimates that the true population mean difference is somewhere between 0.102 and 7.898 (knowing that the estimate could be wrong).
Cohen’s d = 1.633. Given Cohen’s heuristics for interpreting effect sizes, this would be considered an extremely large effect.
For this analysis, the differences between two measurements on one set of people are being compared. Thus, the summary and the inferential statistics focus on that difference.
A paired samples t test showed that the difference in Outcome scores (N = 4) between the first time point (M = 2.00, SD = 2.45) and second time point (M = 6.00, SD = 2.45) was very large and statistically significant, t(3) = 3.27, p = .047, 95% CI [0.10, 7.90], d = 1.63.
Alternatively, the means, standard deviations, and confidence intervals could be presented in a table or figure associated with this text.