# UNIVERSITY OF ARKANSAS AT MONTICELLO SCHOOL OF BUSINESS COURSE SYLLABUS GB 3233 BUSINESS STATISTICS II FALL 2014

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2 3. explain the purpose of hypothesis testing, and the difference between Type I and Type II error, interpret results of statistical software with respect to hypothesis tests of means and proportions, [1] 4. formulate and manually calculate hypothesis tests for one population variance, and for the difference in two population variances, [1] 5. use statistics software to perform hypothesis tests for one population variance, and for the difference in two population variances, [1,3] 6. explain the meaning of analysis of variance, and be able to interpret the results of a single-factor ANOVA, [1] 7. use statistics software to perform a single factor hypothesis test of analysis of variance, and pairwise comparison procedures, [1,3] 8. use statistics software to perform two-factor hypothesis tests of analysis of variance, and interpret the results, [1,3] 9. manually calculate and use statistics software to perform a chi-square test of independence, and chisquare goodness of fit tests, and interpret the results, [1] 10. explain the application of goodness of fit tests, and of tests of independence, [1] 11. manually calculate and use statistical software to calculate X-bar, R, c, and p charts, [1,3] 12. interpret the meanings of the charts calculated in objective 11, and explain their applications, [1] 13. explain the meaning of correlation, use statistical software to calculate correlation coefficients, and to determine the significance of the coefficients, [1,3] 14. demonstrate understanding of the basic concepts underlying simple regression by being able to correctly answer multiple choice questions concerning these concepts, and being able to interpret the results of a simple regression model, [1] 15. use statistical software to calculate a simple linear regression between a dependent and an independent variable, and be able to write out the equation and interpret the result, [1,3] 16. explain at least one use and one misuse of regression analysis, [1] 17. demonstrate understanding of the basic concepts underlying multiple regression by being able to correctly answer multiple choice questions concerning these concepts, and being able to interpret the results of a multiple regression model, [[1,3] 18. use statistical software to calculate a multiple regression model, and be able to write out the equation, [1] 19. discuss potential problems involved in regression and the appropriate steps to deal with these problems, [1] 20. use instrumental (or dummy, or qualitative) variables in multiple linear regression. [1]

6 General Course Outline Class days 1-6 Class days 7-12 Introduction and overview; pretest (for assessment only, not counted towards grade). Review of hypothesis testing for one mean and one proportion Chapter 9, Introduction to Hypothesis Testing Hypothesis tests for 2 population means or proportions Chapter 10, Estimation and Hypothesis Testing For Two Population Parameters Day 13 Exam 1 (September 22) Covers Chapters 9 & 10 Class days tests for population variances Chapter 11, Hypothesis Testing and Estimation for Population Variances OCTOBER 1 BUSINESS DAY Class will convene in Fine Arts Center All students are required to attend Class days Goodness of fit and tests of independence (Chi-square) Chapter 13, Goodness of Fit and Contingency Analysis Day 23 Exam 2 (October 15) Class days Class days Analysis of variance Chapter 12, Analysis of Variance Simple linear regression Chapter 14, Introduction to Linear Regression and Correlation Analysis Day 37 Exam 3 (November 17) Covers Chapters 12 and 14 Class days Final Exam Multiple regression Chapter 15, Multiple Regression and Model Building, pages 612 to 630, and pages Covers Chapter 15 plus comprehensive post-test Thursday, December 11, :30 to 3:30 p.m.

7 Homework Assignments Chapter Problems Due Dates 9 to be announced for all chapters 9-8, 9-12, 9-14 a & b 9-32, 9-36, 9-38, , 10-26, 10-38, 10-42, 10-44, 10-56, , (for 11-10, calculate mean and standard deviation using a spreadsheet program, or from formulas in Chapter 3) 11-26, 11-28, , 13-6, (all groups have an expected value of 5), 13-18, 13-20, All homework done in lab (213) on computer 14 All homework done in lab (213) on computer 15 All homework done in lab (213) on computer

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