The learning diary is for you to check that you have learned the key concepts and principles covered in the course. The list of questions is provided to you on the first lecture and you will work on the answers independently or in small groups if you want. You should work on the learning diary document soon after each class to write down how you understood the content of the classes and lecture materials.
You do not need to write a full essay for each question. One or two short paragraphs per question is sufficient. An ideal length for an answer for each question is about half a page or less.
The list of questions may be updated during the course.
List of questions for the learning diary
What is a statistical model and an estimator? What are the characteristics of good estimators? What kind of assumptions estimators can make and why it is important to test these?
Explain the concepts of estimate, standard error, test statistic, null-hypothesis significance testing, and p-value.
Explain statistical inference and causal inference.
Why are control variables used in management research and what are the characteristics of good control variables and good reporting of control variables?
Explain the concept of endogeneity and how it can be addressed in research.
Explain the workflow of regression analysis.
Explain the concept of nested model comparison and two commonly used nested model tests.
Explain what "linear model implies a correlation matrix" means. Explain what this means for model estimation and give two examples of models that can be estimated from a correlation matrix.
Explain the idea of generalized linear model and when and why you would want to use one.
Why plotting marginal effects of non-linear models is nearly always a good idea.
Explain two strategies for estimating a mediation model. What are the advantages and disadvantages of each?
Explain the concept of reliability based on classical test theory. Explain the two different ways that reliability is commonly assessed in management research.
What specifically does coefficient alpha quantify? What assumptions are required for consistency of coefficient alpha and how these assumptions can be assessed in research?
What is the difference between predictive validity, content validity, and construct validity. Are these complementary or competing ideas?
Explain the latent variable model of validity.
What is the idea of factor analysis? What is the purpose of using factor analysis in management research?
What is common method variance? Give one example of a scenario where and how common method variance could be a problem.
Define experiment, survey research, field research, and archival/ secondary data research. Explain briefly the advantage of each design.
What is a quasi-experiment and why would you want to do one?
When is it appropriate to use a quantitative research design?