The table of descriptive statistics can be used to assist in calculating the correlation.
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 variable.
The tables of inferential statistics show the key elements to be calculated.
Proportion of Variance Accounted For by the Regression Model
Est LL UL
Model 0.250 0.000 0.606
Hypothesis Tests for the Regression Coefficients
Est SE t p
(Intercept) 5.000 1.785 2.801 0.107
Outcome1 0.500 0.612 0.816 0.500
The model summary table shows a final R-Squared (“Est”) of .250. This represents a moderate amount of variance in Outcome 2 accounted for by Outcome 1.
For the test of the regression coefficient associated with Outcome 1, the table shows a t of 0.816 and p of .500. This means that Outcome 1 did not statistically significantly predict Outcome 2.
Regression cofficients provide a measure of statistical relationship between two variables. Note that regression coefficients can also have inferential information associated with them (and that this information should be summarized if it is available and of interest).
For the participants (N = 4), the scores on Outcome 1 (M = 2.00, SD = 2.45) moderately but not significantly predicted Outcome 2 (M = 6.00, SD = 2.45), R2= .250, β = .500, t = 0.816, p = .500.