Lecture L: One-way Analysis of Variance (ANOVA) Text Sections 9.1, 9.2, and 9.3 Testing for difference in the means among several (>2) groups Example A (Cereal)
Acme Food Company wished to test five different package designs for a new breakfast cereal. Fi
STAT 350 Spring 2009
Homework #6 Corrected through Lecture J
Text Exercises Chapter 7, Problems #38, 46*, 48*, 52 * do not assume equal variance! Then answer the following problems 1. You are part of a team that has designed a new filter to be used with p
STAT 350 Spring 2009
Homework #12 covers through Lecture S
1. An ecologist is studying the trade-offs individuals make between investment in survival and growth and the investment in reproduction. In particular she is studying this relationship in a highl
STAT 350 Fall 2008 Final Exam
Your Name: _ Your Seat: _ Section Time (circle): 10:30 12:30 1:30
Note: You are responsible for upholding the Honor Code of Purdue University. This includes protecting your work from other students. Show your work on all ques
Practice for Exam 2 STAT 350 Fall 2008 Exam 2
Your Name: _ Your Seat: _ Section Time (circle): 10:30 12:30 1:30
Note: You are responsible for upholding the Honor Code of Purdue University. This includes protecting your work from other students. Show your
STAT 350: Statistical Methods Spring 2009 Instructor: Dr. Shannon M. Knapp email: knappsm@purdue.edu office: HAAS 114 office phone: 496-9541 mailbox: located in HAAS 164 office hours: Standard Office Hours: MF 1-2 p.m. and W 2-3 p.m. Additional office hou
Lecture T: Regression Diagnostics In this lecture, we will examine some methods for testing some of the important assumptions of regression. Then we will discuss some remedial measures that can be used to remedy violations of these assumptions. Key Assump
Lecture R: Simple Linear Regression Sections 3.3 and 11.1
Example Data: For a science project, a student wanted to examine the effects of alcohol on performance. The student trained mice to run a maze. Once all mice were proficient at running the maze, th
Lecture O: Chi-Square Tests Text Section 8.3 In this lecture, we will explore hypothesis tests for Categorical Data. (1) Bivariate Data: tests for 2-way contingency tables (both variables are categorical) (2) Univariate Data Bivariate Categorical Data: te
Lecture M: Randomized Complete Block Designs Text Section 9.4 Completely Randomized Design (CRD)
Ex.
Want to study effect of 4 formulations of fertilizer (call them A, B, C, and D) on yield in corn. Potential experimental designs: 1. Put seeds in individu