Solutions Manual For Statistical Computing with R 2nd Edition By Maria L. Rizzo ( ) 9781466553323 Chapter 1-15 Complete Questions and Answers A+.pdf

STATn 415:n STATISTICALn COMPUTING




MAIN INFORMATION PAGE
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COURSE PRELIMINARIES n




Statistical analysis and research is becoming more and more complex b
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ecause of the use of more advanced methods and models. This cours
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e aims at introducing students to methods and techniques for performi
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ng such analysis and research, in particular this course focuses the de
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velopment and implementation of statistical algorithms.
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Course Content n


There are Five (5) topics in this course, namely:
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Topic One: Review of R Topic
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Two: Simulation
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Topic Three: Optimization and solutions to nonlinear Equations Topic
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Four: Monte Carlo Integration
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Topic Five: Basic Bayesian Statistics
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Course Leaning Outcomes n n




“Transforming nLivesnthroughnQualitynEducation”
n Egerton nUniversitynisnISOn9001:2008nCertified nPag
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, STATn 415:n STATISTICALn COMPUTING


Upon successful completion of this course, a learner should be able to
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:
Develop algorithms and write R functions to simulate data from d
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iscrete and continuous distributions
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Solve nonlinear equations numerically (Univariate functions) Optimiz
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e univariate functions (perform unconstrained optimization) Approxi
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mate definite integrals using Monte Carlo Methods
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Perform basic Bayesian statistical analysis
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Need Help? n




This course was developed in June 2020 by Obwoge Okenye, Phone:
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+254705081120 Email: . (Lecturer of Statistics i n n n n n n


n the Department of Mathematics at Egerton University). For any help d
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o no hesitate to contact me.
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For technical support e.g. lost passwords, broken links etc. please con
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tact tech-support via e-mail . You can
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also reach learner support through elearner
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.


Assignments/Activities

Assignments/Activities are provided at the end of each topic. Some as n n n n n n n n n n


signments/activities will require submission while others will be self- n n n n n n n n


assessments that do not require submission. Ensure you carefully chec
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k which assignment require submission and those that do not.
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Course Learning Requirements Timel
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y submission of the assignments
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2 CATs (30%) –
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nCAT 1 marks are derived from assignments. Final Examination (
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“Transforming nLivesnthroughnQualitynEducation”
n Egerton nUniversitynisnISOn9001:2008nCertified nPag
e n2nofn134

, STATn 415:n STATISTICALn COMPUTING

70% of total score)
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“Transforming nLivesnthroughnQualitynEducation”
n Egerton nUniversitynisnISOn9001:2008nCertified nPag
e n3nofn134

, STATn 415:n STATISTICALn COMPUTING

A working Laptop
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Self-assessment
Self-
assessments are provided in order to aid your understanding of the to
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pic and course content. While they may not be graded, you are strongl
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y advised to attempt them whenever they are available in a topic.
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“Transforming nLivesnthroughnQualitynEducation”
n Egerton nUniversitynisnISOn9001:2008nCertified nPag
e n4nofn134