## STAT 401A: Statistical Methods for Research Workers Ag. and Bio. Sciences Spring 2015 SYLLABUS and other useful information

 Lectures: MWF 9-9:50am, 1126 Sweeney Laboratory: T 12:10 - 2 pm, 2272 Gilman Instructor: Philip Dixon pdixon at iastate dot edu 2121 Snedecor Hall Ames IA 50011-1210 4-2142 Office Hours: M 3-4, Tu 4-5 TA/grader Nehmias Ulloa TA office hours: W 3-5, 3404 Snedecor Questions:: Please feel free to e-mail ( pdixon at iastate dot edu or nulloa1 at iastate dot edu) anytime with questions or comments. Objectives: By the end of the course, students should be able to analyze and interpret data from experimental studies using parametric and non-parametric methods. Students should be able to appropriately use statistical methods for comparisons of two groups, comparisons of multiple groups, and relating a response to one or more continuous variables. Students should understand how features of the study design influence the choice of statistical method and the type of conclusions that are appropriate. Students should recognize the conditions necessary for an appropriate statistical analysis, how to check if those conditions are met and understand the consequences of violating those conditions. Text: Ramsey, F.L. and Schafer, D.W., 2012. The Statistical Sleuth, 3rd ed. Duxbury SAS info:(both optional) Elliot, R. J., 2009. Learning SAS in the Computer Lab. 3rd ed. Cengage Learning Delwiche, L. D. and Slaughter, S. J. 2012. The Little SAS book, 5th ed. SAS Institute Press Goals: 1) Understand variation and its consequences for drawing conclusions from data.  2) Be familiar with some standard statistical methods:        when and how to use them,        how to use statistical software,        how to interpret statistical results. 3) Be able to apply statistical principles to novel problems.  This class emphasizes the appropriate analysis of experimental data. I presume you will be using class material within the next year. If it will be two or three years before you analyze data, I suggest you delay taking 401. Grading: Weekly Homework: 120 pts  Two Midterms: 100 pts each  Final: 130 pts Course Outline (proposed):
 Week Dates Chapter Topic 1 Jan 12-16 1 Types of studies, Statistical Inference, Data summary Jan 19, Martin Luther King Day No class 2 Jan 21-23 2 Comparison of two groups:     Hypothesis tests 3 Jan 26-30 2 Confidence Intervals 4 Feb 2-6 4 Nonparametric methods 5 Feb 9-13 3 Assumptions and robustness 6 Feb 16-20 5 Comparison of multiple groups 7 Feb 23-27 6 Linear combinations and multiple comparisons Feb 24 MIDTERM I In lab 8 Mar 2-6 6 False Discovery Rate, Choosing a method 9 Mar 9-13 7, 8 Linear regression Mar 16-20 Spring break, no class 10 Mar 23-27 8, 9 Lack of Fit, Correlation, Multiple Regression 11 Mar 30 - Apr 3 9, 10, 11 Multiple regression (cont.) 12 Apr 6-10 12 Model selection Apr 7 MIDTERM II in lab 13 Apr 13-17 13,14 Two-way ANOVA (intro) 14 Apr 20-24 18, 19 Contingency tables 15 Apr 27 - May 1 20, 21 Logistic regression May 4 (tentative) Final exam 7:30 am

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