Teaching Undergraduate Econometrics: A Suggestion for Fundamental Change
Contrary to the belief of most econometrics instructors, upon completion of introductory statistics courses the vast majority of students do not understand the basic logic of classical statistics as captured in the sampling-distribution concept. They have learned to do mechanical things such as compute a sample variance, run a regression, and test an hypothesis, and they know they can pass the course by remembering how these techniques work. They view statistics as a branch of mathematics because it uses mathematical formulas, so they look at statistics through a mathematical lens. What they are missing is the statistical lens through which to view this world, allowing this world to make sense. The sampling-distribution concept is this statistical lens. My own experience discovering this lens was a revelation, akin to the experience I had when I put on my first pair of eyeglasses: suddenly everything was sharp and clear. In this paper I discuss this issue and suggest a means whereby instructors of undergraduate econometrics courses (i.e., following introductory statistics) can provide the missing statistical lens.
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