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Tags What are tags? Add a tag. Public Private login e. Add a tag Cancel Be the first to add a tag for this edition. Lists What are lists? Login to add to list. Be the first to add this to a list. Comments and reviews What are comments? Add a comment. Federation University Australia Library. RMIT University. University of Tasmania. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results.
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The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitable for a second course in applied statistics with every method explained using SAS analysis to illustrate a real-world problem. Kenneth J.
Summation exercises and a historic data analysis. Homework 5. Probability exercises and an application to a randomized experiment. Homework 6. Variance, covariance and standard errors for fitting a linear model.
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Homework 7. Using a linear model for investigation of two populations. Homework 8. Making an F test, and exploring the t and F distributions. Homework 9. Analyzing a dataset: Investigating variables associated with hospital-acquired infection. Lab 3. Using matrices for fitting a linear model by least squares.
Lab 4. Summation and quiz review. Sample quiz. Lab 6. Variance, covariance and standard errors for the linear model. Lab 8. Confidence intervals and hypothesis tests. Lab 9.
Lab Review for Quiz 2. Final review. Solutions for the exercises. Quiz 2 will have 4 questions, with one question of each type normal approximations; prediction; estimates and confidence intervals; F-tests drawn randomly.
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A list of questions in the quiz 2 generator with some solutions. The style and format of the final exam will be based on the practice final exam below. The exam will work through a data analysis, asking questions to requiring understanding of the statistical techniques used, how they are computed, and how they are interpreted.
Practice final exam , with solutions for questions not discussed in class. Revised course version Course description Course information Grading Class notes Homework assignments Lab materials Quiz materials Midterm exam materials Final exam materials.
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Course description An intermediate course in applied statistics, covering a range of topics in modeling and analysis of data including: review of simple linear regression, two-sample problems, one-way analysis of variance; multiple linear regression, diagnostics and model selection; two-way analysis of variance, multiple comparisons, and other selected topics. Thu pm. GSI: Yuan Sun yuansun umich.
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