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STATS 10 Introduction to Statistical Reasoning

Course Description

Lecture, Three Hours; Discussion, One Hour; Computer Laboratory, Two Hours. Preparation: Three Years Of High School Mathematics. Not Open For Credit To Students With Credit For Course 11, 12, 13, 14, Or Former Course 10h. Introduction To Statistical Thinking And Understanding, Including Strengths And Limitations Of Basic Experimental Designs, Graphical And Numerical Summaries Of Data, Inference, Regression As Descriptive Tool. P/np Or Letter Grading.

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STATS 100A Introduction to Probability

Course Description

Lecture, Three Hours; Discussion, One Hour. Requisites: Mathematics 32b, 33a. Not Open To Students With Credit For Electrical Engineering 131a Or Mathematics 170a; Open To Graduate Students. Students May Receive Credit For Only Two Of Following: Course 100a, Former Course 110a, Biostatistics 100a. Probability Distributions, Random Variables, Vectors, And Expectation. P/np Or Letter Grading.

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STATS 100B Introduction to Mathematical Statistics

Course Description

Lecture, Three Hours; Discussion, One Hour. Requisite: Course 100a Or Mathematics 170a. Survey Sampling, Estimation, Testing, Data Summary, One- And Two-sample Problems. P/np Or Letter Grading.

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STATS 100C Linear Models

Course Description

Lecture, Three Hours; Discussion, One Hour. Requisite: Course 100b. Theory Of Linear Models, With Emphasis On Matrix Approach To Linear Regression. Topics Include Model Fitting, Extra Sums Of Squares Principle, Testing General Linear Hypothesis In Regression, Inference Procedures, Gauss/markov Theorem, Examination Of Residuals, Principle Component Regression, Stepwise Procedures. P/np Or Letter Grading.

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STATS 110A Applied Statistics

Course Description

Lecture, three hours; discussion, one hour. Requisites: course 35A or 35B or 35C and Mathematics 3B or 31B, or Mathematics 32B and 33A. Not open to students with credit for Electrical Engineering 131A. Students may receive credit for only two of following: courses 100A, 110A, Biostatistics 100A. Probability, distributions, expectation, estimation, central limit theorem, confidence intervals, testing. P/NP or letter grading.

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