MA 262 - Probability and Statistics

• Be familiar with the terminology and nomenclature of both probability and statistics
• Know the difference between a parameter and a statistic
• Know the difference between a population and a sample
• Understand the basic concepts and properties of probability
• Understand the meaning and significance of the standard deviation
• Calculate the mean and variance of probability distributions
• Be familiar with, and able to calculate probabilities of, the binomial, Poisson, Normal, Student-t, Chi-square, and F distributions
• Construct appropriate confidence intervals for population parameters
• Have a basic familiarity with the Central Limit Theorem and realize that it affects the calculations of test values and confidence intervals
• Perform hypothesis tests concerning the means, variances, and proportions of one or two populations
• Perform hypothesis tests concerning the comparison of means of more than two populations

• Algebra
• Trigonometry
• Differentiation of algebraic and transcendental functions
• Integration of algebraic and transcendental functions

• Measures of central tendency and dispersion (2 classes)
• Introduction to probability and the laws of probability (2 classes)
• Discrete probability distributions: binomial and Poisson (4 classes)
• Introduction to the Central Limit Theorem (1 class)
• Continuous probability distributions: normal, t, chi-square, and F (3 classes)
• One-sample hypothesis testing and statistical inference (5-6 classes)
• One-sample confidence intervals and statistical inference (2-3 classes)
• Two-sample confidence intervals and statistical inference (3 classes)
• Two-sample hypothesis testing and statistical inference (4 classes)
• Analysis of variance (3 classes)
• Exams (2 classes)