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This is a common approach in some introductory statistics textbooks. The alternative hypothesis can be directional (e.g., $H_a : \mu > \mu_0$) or non-directional (e.g., $H_a : \mu \ne \mu_0$), but the …

You can assess if there is a statistically significant change in the coefficient of determination between the models with and without the two independent variables. For each model (#1 the smaller and …

For a problem like this, the basic comparison being assessed is if the probability is statistically different from 50%. Using the NHST notation $$H_0: \pi = 0.5$$ where $\pi$ is the probability of usi …

In brief, I am used to a definition of the P-value as: the probability of observing our sample data (or something more extreme) if the null hypothesis is true. Consequently, seeing null hypotheses of …

Based on the alternative hypothesis, the 95% confidence range would be the left-tailed (lower 95%) region. If after you obtain your bootstrapped estimates, if your value of $c$ from the hypotheses doe …

If you have enough data to assess daily vs. hourly rates, I am going to assume you have enough data to split the data in half. Because linear regression assumes a constant slope (which I assume you b …

If I were asked to "prove" (i.e., statistically confirm using some null hypothesis statistical testing (NHST) protocol) that one category for a categorical variable was maximal for a sample (from a si …

First, I will preface this question with my ulterior motive: I would like more evidence that the use of 19th and 20th century approximations play little to no pedagogic advantage in modern intro stats …

Here is a very brief primer for 2x2 contingency tables. First, it is necessary to think about the way the data can be presented. One approach is to fill in a 2x2 contingency table where the columns i …

My recommendation would be a multi-level logistic multiple regression model where the dependent variable is having obtained the shot or not, the independent variable would be pre/post (dummy coded as …

The commenters have provided the answer...I'll enter it here. The first output is presenting the P-values for each individual coefficient in the model. For this output, this can be interpreted with …

This is a clever question, and demonstrates careful consideration of the algorithms we use and why. And the analysis of power is indeed a key motivator in deciding which test to use. However, in this …

If you wish to test if two correlations from two samples for independent pairs of variables are different from each other, the null hypothesis statistical test (NHST) appropriate for this would be the …

Yes, the Fisher z-transform would be a reasonable test (even if the underlying distributions are non-normal). The reason for this is that the distribution of the correlation coefficient is nearly no …

The formal answer to this question is "yes", the ANCOVA test requires homogeneity of slopes (equal slopes for the groups). But with regards to the underlying motivation for the question, the answer i …