Hi,
Can someone help me to understand the null/alternate hypothesis test in effect summary and parameter estimate table?
is there document explain it with equation?
Thanks
I may be running the risk of oversimplifying, but the null hypothesis is NULL because it takes the stance of "no effect" or "no difference". For parameter effects, that means the null hypothesis is "This factor has no effect" which means "The parameter estimate for this effect equals zero."
The alternative hypothesis is the opposite of the null. So, "this parameter estimate is different than zero."
I'm getting confused.
1)it looks like both hypothesis test in Effect Summary and Parameter Estimate is testing "no effect".
my question:
1) what is the t-test equation for these 2 tests?
2) what these 2 type of hypothesis test against - Effect summary hypothesis (Pvalue)
- Parameter estimate (Prob>|t|)
In general, test of significance (p-values) are tests based on rejecting or not rejecting the Null Hypothesis. The p-value is the associated probability of a Type 1 or alpha error (rejecting the Null when the Null is true). These tests can be done on different statistics with different associated probability distributions (e.g., t, F, Chi square, etc). The Parameter Estimates reports the coefficients of the model and Prob>|t| is the probability a value greater than the calculated t Ratio (Estimate/Std Error) could exist by chance alone (this is actually area of the probability distribution, in this case Student's t-distribution beyond the calculated test statistic) . Effects tests use the calculated F ratio (mean square effect/mean square error) in the same way. The Prob>F is the probability a value greater than the calculated F-Ratio could exist by chance alone (i.e., when the effect = 0).
This picture might clarify graphically what is being calculated.
I still don't get the "mean square effect/mean square error" related to the P value in effect summary.
Please refer to the attachment. This is the Pvalue in Effect summary table. Can you help me to understand how individual effect's pvalue is calculated?
