Basic Statistical Concepts
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Econometrics pp Cite as. One chapter cannot possibly review what one learned in one or two pre-requisite courses in statistics. This is an econometrics book, and it is imperative that the student have taken at least one solid course in statistics. The concepts of a random variable, whether discrete or continuous, and the associated probability function or probability density function p. Similarly, the reader should know the following statistical terms: Cumulative distribution function, marginal, conditional and joint p. The reader should be comfortable with computing mathematical expectations, and familiar with the concepts of independence, Bayes Theorem and several continuous and discrete probability distributions. Unable to display preview.
Course Description This course is designed primarily to provide the necessary statistics background to incoming PhD students in the economics department, in particular so that it might be possible to continue with the more challenging econ and econ in the first year econometrics sequence. You are required to be familiar with the materials taught in econ A and econ B. You also need to be very good at linear algebra and multivariate calculus, and should know some basic real analysis. Part 2 of econ introduces the statistical inference theory of estimation and testing. Time permitting, an introduction to basic linear regression models might be given. Textbooks and Reading Materials I will be drawing materials mostly from the following three books. As long as you can survive the course, it is entirely up to you to decide whether you want to purchase all, one, or none of these books.