Monday, August 20

• Introduction (presented in lecture)

Wednesday, August 22

• Five Number Summary & Sample Variance/Standard Deviation
  
• Descriptive statistics: a few practice problems and answers.

Friday, August 23

• Data collection
• Experiments vs. observational studies examples

Monday, August 27

• Sampling distribution lecture notes
• Worksheet on sampling distributions and the 100 boxes-handout

Wednesday, August 29

• One sample t-tests overview

Friday, August 31

• Lecture notes on matched pairs studies
• Exercise on t tests for matched pairs

Wednesday, September 4

• Matched pairs or not? Examples discussed in class
• Example of a two-sample problem.
• Two sample inference(construction of confidence intervals and t-tests)

Friday, September 6

• Notes on randomization tests (covered in class)
• You can find here a general summary for randomization tests

Monday, September 10

• A summary of the discussion of the assumptions regarding t-tools inference

Wednesday, September 12

• A general discussion of the logarithmic transformation
• An example of a problem using the logarithmic transformation (with solutions)
• Another practice problem using the log transformation (problem 31, page 81, from the textbook) (discussed in Lab 4)

Monday, September 17

• General construction of the rank-sum test and
• an example (covered in class)
• SAS and R commands and output for the rank-sum test

Wednesday, September 19

• Additional exercises for the rank-sum tests

Friday, September 21

• General construction of the sign and signed-rank test and
• an example (covered in class)

Monday, September 24

• How do I decide which test to use?(covered in class)

Wednesday, September 26

• General construction of the one way analysis of variance and F-test (covered in class) and
• an example

Friday, September 28

• one way ANOVA table
• R code and output for the doughnuts problem and SAS code and output

Monday, October 8

• An alternative point of view: F-test as a comparison between the full and reduced model

Wednesday, October 10

• Inference for linear combinations of means

Friday, October 12

• Contrasts for testing for linear trend (example covered in class)
• An overview of contrasts for testing for linear trend.

Monday, October 15

• Adjustments for multiple comparisons: general discussion, and an example covered in class.
• An example (comparison of the contents of cholesterol of the yolk of chicken) and the SAS code (chicken.sas)

Wednesday, October 17

• Linear correlation coefficient

Friday, October 19

• Introduction to least squares regression line
• A few practice examples for constructing the least squares regression line

Monday, October 22

• Inference for Simple Linear Regression with an example (covered in class)
• A more detailed explanation regarding inference for SLR
• Another example ( black wheateaters) regarding estimation and inference for SLR (covered in Lab)

Wednesday, October 24

• Confidence and Prediction Intervals for Simple Linear Least Squares Regression (covered in class)
• SAS code and output for prediction and confidence intervals.

Friday, October 26

• More on residuals and diagnostics for SLR
• A few examples regarding checking assumptions and diagnostics for SLR. An example using SAS.
• Interpretation of the Slope of the Least squares regression line

Monday, October 29

• ANOVA table for SLR (covered in class) and a graphical illustration (covered in lab)

Wednesday, October 31

• Lack of fit for simple linear regression and some illustrative graphs

Friday, November 2

• Introduction to multiple linear regression, SAS code and output and R code and output

Monday, November 5

• Introduction to the use of indicator variables in multiple linear regression (worksheet)
• Graphical illustration
• SAS output
• R code

Monday, November 12

• Variable selection:
  • SAS code and output based on the SAT case-study in Chapter 12 of the Statistical Sleuth: sat.sas and sat_output.pdf
  • Data set: sat.txt.
  • R code: sat.r.

Friday, November 16

Data set anscombe.txt, R code anscombe.r, SAS code anscombe2.sas and the associated graphs and output for the discussion on influential points (Chapter 11)

Monday, November 26

• Introduction to two-factor analysis of variance and some plots illustrating the concept of interaction
• The data set (feederfloor.txt) used as an example and the R code(feeder_trough.r)

Wednesday, November 28

• More about two-factor analysis of variance (and answers) and the corresponding interaction plots
• Some more SAS code to use in situations where interaction is present and important ( using slicing)
• A similar data set (Inoculation.txt) to the one used in class.

Friday, November 30

• Means vs. Least Squares Means

Monday, December 3

• An introduction to the analysis of Randomized Complete Block Designs (RCBD) and some (answers)