I am looking at the correlation between daily population and daily incidents in a detention center. I created a measure that dynamically shows the correlation coefficient and what kind of relatinship it shows. I want to also do a hypothesis test to calculate the significance using the p value. How can I create a measure to have this dynamically show on my dashboard? This is how to caluclate it by hand:
I don't feel comfortable sharing my screen because I deal with confidential information.
| Sample Correlation (r)(r) = | .09. |
| Sample Size (n)(n) = | 7000 |
| Significance Level (\alpha)(α) = | .05 |
Null and Alternative Hypotheses
The following null and alternative hypotheses need to be tested:
null hypothesis- correlation equals zero
alternative hypothesis- correlation does not equal zero
where \rhoρ corresponds to the population correlation.
The sample size is n = 7000, so then the number of degrees of freedom is df = n-2 = 7000 - 2 = 6998
The corresponding critical correlation value r_crc for a significance level of α=0.05, for a two-tailed test is:
t===r1−r2n−20.091−0.0927000−27.56
The p-value is computed as follows:
p==Pr(∣t6998∣>7.56)<.0001
Since we have that p < .0001, it is concluded that the null hypothesis is rejected.
Therefore, based on the sample correlation provided, it is concluded that there is enough evidence to claim that the population correlation is different than 0, at the α=.05 significance level.
