1 Does the quality of a lecture affect exam results?

You are goign to use some simulated data available in openintro. This data (classdata) represents students’ scores from three different lectures that were all given the same exam.

The first thing to do is use the skim command (package skimr) to just have a quick look at the classdata data. The data is available in the openintro package, so you’ll need to install and load this. We first did this in session 3. We used skim back in session 1. If you are having problems with skim (Mac X11 or Rcurl), I’d just use base R, summary()

Next you want to have a visual check to see if lecture had an effect on exam performance (m1). Plot exam performance (y-axis) using a boxplot with lecture as the x-axis. You encountered boxplots back in session 2.

1. Blackboard MCQ: Based just on your intial work above, which lecture is the best?

In the lecture, I build a model called model_weight. You can build one called model_exam (or anything you like, it’s just a name). model_exam should look at the effect of lecture on exam result.

2. Blackboard MCQ: Correctly (as described in the slides) report the results of your ANOVA for the effects of lecture on exam result.

If your data was not normal, the first thing to try would be to normalise it by transformation. But don’t do that, rather as an exercise I would like you to use nonparametric tests to carry out the same analysis. Does lecture have an effect on exam result Kruskal-Wallis. And if so which lecture was the best Dunn’s test.

3. Blackboard MCQ: Are the results of the non-parametric analysis qualitatively different than the parametric analysis’ results?

2 Does IQ affect GPA results?

More simulated data available in openintro. This data (gpa_iq) represents students’ IQ scores and gpa exam scores. So the relationship between intelligence, if that’s what IQ measures, and academic achievement in secondary school.

Next you want to have a visual check to see if IQ (iq) had an effect on exam performance (gpa). Plot exam performance (y-axis) using a scatterplot with IQ as the x-axis. You encountered scatterplots (geom_point) back in session 2.

4. Blackboard MCQ: Based just on your initial work above, how does IQ affect GPA?

In the lecture, I build a model of how tannin affects growth. You can build one called model_iq (or anything you like, it’s just a name). model_iq should look at the effect of IQ on GPA. Remember ~ in R means depends on. So gpa~iq, says GPA depends on IQ, exactly what we want here.

5. Blackboard MCQ: What is the equation of the line of your regression for the effects of IQ on GPA.

6. Blackboard MCQ: Correctly (as described in the slides) report the statistics of your regression for the effects of IQ on GPA.