Descriptive statistics, basic concepts of probability and sampling with the aim of introducing fundamental notions and techniques of statistical inference.

Prerequisite: Math 10 or a score of 51 or higher on a proctored ALEKS PPL exam.

Prepares students for STAT 10B that requires background in data analysis process, descriptive statistics and the concept of randomness. Topics include: Summarizing the data distribution graphically and numerically; reasoning about bivariate numerical data; linear correlation and regression; linear, quadratic and exponential functions as a way of modeling a correspondence between two variables; reasoning about bivariate categorical data; basic concepts of probability and the law of large numbers; conditional probability; discrete random variables; binomial distribution; and an introduction to continuous random variables. Lecture three hours.

Continuation of STAT 10A. Stat 10B prepares students for research methods applications/ courses in various disciplines. Topics include: Continuous random variables and normal distribution; sampling distributions and the central limit theorem; confidence intervals and tests of hypotheses for means, proportions, difference in means and difference in proportions; and chi-squared tests for categorical data analysis. Lecture three hours.

Prerequisite: STAT 10A

Sample spaces, combinatorics, and random variables. Density and distribution functions. Expectation, variance, and covariance. The binomial, uniform, poisson, negative binomial, hypergeometric, exponential, gamma, beta, and normal distributions. Sampling distributions, estimation, and hypothesis tests. Students are given periodic writing assignments which encourage them to think through concepts of the course.

Prerequisite: MATH 26A, MATH 30, or appropriate high school based AP credit.

Probability axioms, discrete and continuous random variables, functions of random variables, joint densities, expectation, moment generating functions. Chebyshev's inequality, transformations, weak law of large numbers, central limit theorem.

Prerequisite: MATH 31 and either STAT 1 or STAT 50

Computer methods for accessing, transforming, summarizing, graphing and making statistical inferences from data; focus is on command-line statistical software, but menu-driven software may be introduced; application of computer methods to solve problems selected from the areas of modeling, simulation, inference and statistical learning.

Prerequisite: (STAT 1 or STAT 50) and (MATH 26A or MATH 30) or consent of the instructor.