Variable Y D_R_1 D R 1 Variable X D_FAST_G D FAST G Sample size 100 Correlation coefficient r 0.08176 Significance level P=0.4187 95% Confidence interval for r -0.1165 to 0.2738 WHAT DOES THIS MEANING
Correlation Analysis Interpretation
This is a Pearson correlation analysis between two variables. Here's what each part means:
The Variables
- Variable Y: D_R_1 → likely "Diet, Rest, Day 1" or a similar coded outcome measure
- Variable X: D_FAST_G → likely "Diet, Fasting, Group" or a similar coded predictor
The Results Breakdown
| Statistic | Value | Meaning |
|---|---|---|
| Sample size (n) | 100 | 100 observations/participants were analyzed |
| r = 0.08176 | Very weak positive correlation | As X increases, Y barely tends to increase |
| P = 0.4187 | Not significant | There is no statistically significant relationship |
| 95% CI: -0.1165 to 0.2738 | Crosses zero | The true correlation could be negative, zero, or positive |
What This Means in Plain Language
-
The correlation is essentially zero — r = 0.08 is extremely weak. On a scale of -1 to +1, this is negligible.
-
The result is NOT statistically significant — P = 0.4187 is far above the standard threshold of P < 0.05. This means the weak relationship observed could easily be due to random chance.
-
The confidence interval crosses zero (-0.1165 to 0.2738) — this confirms there is no reliable direction to the relationship. The true correlation might be negative or positive; we cannot tell.
Bottom Line
There is no meaningful or statistically significant linear relationship between D_FAST_G and D_R_1. The two variables appear to be independent of each other in this sample of 100.
If these are part of a study, this finding suggests that the fasting group variable does not predict or correlate with the rest/recovery outcome at Day 1.
This is a shared conversation. Sign in to Orris to start your own chat.