Wanda Martina Morris
Prerequisite: permission of Graduate Program Coordinator. Offered: AWSpS.
This is a mid-level introduction to the basic concepts and methods of Statistics. Some probability and calculus (in particular, derivatives and integrals) will be reviewed. The course covers methods of quantitative data collection (observational studies and experiments) descriptive statistics, and the theory and methods of basic statistical inference.
Student learning goals
Critically evaluate the quality of the quantitative data used in scientific and lay contexts.
Understand the principles of exploratory data analysis (EDA) and statistical graphics.
Know and be able to calculate the most common numerical summary statistics. Know and be able to use the rules for expectations and variances.
Derive the most common probability calculations used in elementary statistics.
Understand the differences between probability distributions, population distributions, sampling distributions, and the role each plays in statistical inference.
Be able to perform basic tasks of statistical inference: construct confidence intervals, conduct hypothesis tests, compute required sample sizes, conduct ANOVA and simple linear regression, and chi-squared tests.
General method of instruction
Lecture, lab, electronic practice problems with immediate feedback, electronic homework with immediate feedback, graded written homework, and review sessions before the midterm and final exam.
Good working knowledge of algebra.
Class assignments and grading
9 weekly homeworks - a combination of end of chapter problems and synthetic problems. The best 7 will count towards the grade.
Lab Assignments: 10% Homeworks: 30% Midterm: 30% Final: 30%