Learning objectives: Literacy or computing?

I recently met two colleagues to solicit their advice on course creation, and the first thing they asked me was ‘are your students expected to run the models themselves?’

My first gut answer was ‘no’ – I want to focus on developing students’ statistical reasoning and literacy. What did the original course creators have in mind? The course description is:

Biostatistics for health science professionals. Concepts and methods, including confidence intervals, ANOVA, multiple and logistic regression, and non-parametric analyses. Scientific literature is used to provide a comprehensive context in which analytical evidence is employed to support practices in the health sciences.

The last sentence seems to imply a focus on literacy, but does ‘methods’ imply computation? The course objectives are that students in the course will learn to:

  • Apply biostatistical concepts, including: probability, distribution, confidence intervals, inference, hypothesis testing, P-value and confidence interval.
  • Apply numerical, tabular, and graphical descriptive techniques to health sciences data. 
  • Conduct appropriate statistical procedures to test null hypotheses.
  • Appraise statistical results in health science research articles and reports. 

Again, ‘appraise’ strikes me as a desire for literacy, but ‘conduct’ seems a clear indicator that computing is also an expectation. However, the weekly learning objectives from units focusing on ANOVA, multiple linear regression, and logistic regression paint a different story:

  • Interpret estimates from a one-way and two-way analysis of variance. 
  • Appraise procedures used to address the problem of multiple comparisons. 
  • Explain prediction models that are grounded in the population regression line.
  • Interpret regression coefficients from a multiple regression model. 
  • Calculate and interpret chi-square test statistics.
  • Interpret results from unadjusted logistic regression models.
  • Identify the reasons for conducting a non-parametric test.
  • Interpret estimates from non-parametric tests including the Wilcoxon Signed-Rank test, the Wilcoxon Rank Sum test and Kruskal-Wallis test. 

‘Interpret’, ‘Appraise’, ‘Identify’, and ‘Explain’ all seem like literacy skills to me, and the only computation that is being asked is a chi-squared test statistic, as well as (in other weeks) odds ratios, risk ratios, relative risks, and other descriptive statistics.

Perhaps this is the right place to draw the line between computation and literacy – I will ask my students to ‘compute’ descriptive statistics, but focus on literacy with regards to inference, modelling, and hypothesis testing.

I am curious though if it is possible to focus on both literacy and computation in the same course. I imagine students becoming stressed and annoyed with debugging with whichever software we might use. Whichever software I do choose ought to be able to do all the calculations I expect students to do in 2117 and 3117, and should be used in both courses.

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