
MA 262  Probability and Statistics3 lecture hours 0 lab hours 3 credits Course Description This course provides a basic introduction to the laws of probability needed to perform statistical analyses. Both descriptive and inferential statistics are considered. Probability distributions, the Central Limit Theorem, confidence intervals, hypothesis testing, and analysis of variance are considered in depth. Note: students cannot receive credit for both MA 262 and MA 3611 . (prereq: MA 137 ) Course Learning Outcomes Upon successful completion of this course, the student will be able to:
 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, Studentt, Chisquare, 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
Prerequisites by Topic
 Algebra
 Trigonometry
 Differentiation of algebraic and transcendental functions
 Integration of algebraic and transcendental functions
Course Topics
 Measures of central tendency and dispersion
 Introduction to probability and the laws of probability
 Discrete probability distributions: binomial and Poisson
 Introduction to the Central Limit Theorem
 Continuous probability distributions: normal, t, chisquare, and F
 Onesample hypothesis testing and statistical inference
 Onesample confidence intervals and statistical inference
 Twosample confidence intervals and statistical inference
 Twosample hypothesis testing and statistical inference
 Analysis of variance
Coordinator Ron Jorgensen
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