Statistics 515 - Statistics I

First semester of a two-semester sequence. Emphasis given to probability theory necessary for application to and understanding of statistical inference. Probability models, sample spaces, conditional probability, independence. Random variables, expectation, variance, and various discrete and continuous probability distributions. Sampling distributions, the Central Limit Theorem and normal approximations. Multivariate calculus introduced as needed. Prerequisites: MATH 132, or 136. (Gen.Ed. R2)

[Note: Because this course presupposes knowledge of basic math skills, it will satisfy the R1 requirement upon successful completion.]

MATH 132 w/ C Note: Math 233 is required for this course.
Note: 35 seats reserved for math and computer science majors

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