This is an university level course in probability and statistics. Students should enroll in this course as a study guide for an university level statistics course or as a refresher course for using statistical analysis in their profession or job. It is unique in that it offers a probability based approach which aids the student in more deeply understanding statistics. No prior knowledge of statistics is required, but a knowledge of calculus would be useful. While there is no required text for this course, the book "Probability and Statistical Inference", ninth edition by Hogg, Tannis and Zimmerman would be an useful accompaniment. There are no formal test or assignments, rather a series of problem sets with solutions. While there are no videos, test or formal assignments, the course consists of three Word documents: lecture notes, problems sets and solutions. At the end of this course, a professional should be ready to start their own statistical analysis and a student to pass their examination.
The course is divided into several sections. The first section covers probability theory. Topics include: properties of probability; combinations and permutations; conditional probability; independent events; Bayes' Theorem. The second section covers discrete distributions such as the binomial, negative binomial and Poisson distributions. The third section covers the normal distribution, exponential and gamma as well as the chi-square distributions. The section on bivariate distributions covers bivariate distributions of both the discrete and continuous types in addition to the correlation coefficient. The highlights of the section on distributions of functions of several variables are the Central Limit Theorem, the moment-generating function, and Chebyshev's inequality. The section on descriptive statistics covers methods of initial exploratory data analysis. The next few sections cover regression analysis, confidence intervals for means, difference of two means and proportions in addition to hypothesis testing about means, proportions and the Chi-Squared Goodness of Fit Test. The section on analysis of variance covers one-factor and two-way analysis and general factorial designs.
The instructor's name is Juliet Howland and she is the Founder and CEO of DJH Tutoring.. She has five years of tutoring experience in math, statistics and economics. She holds a completed M.A. in Economics with a strong math component. She has also completed doctoral coursework in economics with a specialisation in mathematical economics. I am located in Canada.
Language of instruction: English