In order to increase the proportion of explained variation of Pleasure, a dummy variable, Female, expressing Gender (1 for Female, 0 for Male) was added as an explanatory variable to the model described in Question 16

Using a common level of significance it is true that

A new model was considered:

(Good and Blended being dummy variables that identify the students that have a Good background in statistics and the ones that prefer the blended method)

With α=0.10, besides stating that the Understanding level significantly increases Pleasure, I would also state that Pleasure level is significantly 

A Regression Analysis was run with a sample of size 40 to validate the following simple model

with the following estimates (some information is missing):

Is the model significant with α=0.05 ?

The coefficient of correlation between Pleasure and the Bernoulli variable that identifies Statistics III students, computed with the sample of size 40 is 0.04.

We ran an ANOVA with the same sample in order to test Ho: μ_{StatisticsIII} = μ_StatisticsII. 

Infer about the p-value of this ANOVA.

The coefficient of correlation, computed with the same sample (n=40), between Pleasure and Frustration, is -0.39.

Is this model

significant with α=0.05 ?

If instead of the 39 students only 37 would have answered, with this distribution

The number of students that would react with a "Not really" and a blended method preference if both variables would be independent is approximately

A Contingency Analysis was run with this sample 

The test statistic was computed (8.9) and α=0.05.

This ANOVA was run

with an additional factor: Gender (Female and Male).

With α=0.10 what would your conclusion be ?