Review Lesson 2
Lesson2 Review
Sec 2.1 and 2.2
Inference about slope 1 and intercept 0
Inference is two fold here
Estimation via confidence intervals (CI)s
Testing of hypotheses via t statistic
Note that both CI calculations and testing of hypotheses a
Stat 502 Solutions for Review for Exam 1
Grading note: Hypotheses are expressed in this key in terms of means, but the alternative form of
H 0 : all i =0
stating null hypothesis in terms of treatment effects (e.g.
) are accecpted if the
Model containing t
Stat 502 Exam 1 Review
(Assume =0.05 for the exam unless otherwise stated).
For equations, you can use terms like mu_i for
i
to save time if using text editors like word.
1) A study was conducted to evaluate the effect of three different drugs on blood ch
Project Assignment STAT 502 WD
The individual projects are intended to give you a chance to work with ANOVA in a setting of interest to
you. The task is to find or generate a dataset and run an ANOVA. Note: if you elect to generate data
for your project,
Data Analysis (Week 2) Guide
Omair Khan
January 21, 2016
Introduction
How to use this guide
After working on the solutions for this assignment, I realized that many of you may not have worked with
functions in R before. While the book gives two examples o
Lesson2 Review
Sec 2.1 and 2.2
Inference about slope 1 and intercept 0
Inference is two fold here
Estimation via confidence intervals (CI)s
Testing of hypotheses via t statistic
Note that both CI calculations and testing of hypotheses are done for
popu
Week 4 Notes
6 Linear Model Selection and Regularization
6.1 Subset Selection
6.1.1 Best Subset Selection
Fit all p models that contain exactly 1 predictor, all pC2 that contain 2 predictors, etc
Total of 2p possible models
6.1.2 Stepwise Selection
Forwar
5.1 Cross Validation
5.1.1 Validation Set Approach
- Data is divided into 2 parts (Training and Validation sets)
- Model is fitted on the training and the fitted model is used to predict responses in the validation set.
- Validation set error rate (typica
Residual Analysis- checks for validity of 4 assumptions (LINE), detects outliers and model inadequacy
To get the plots in Minitab: stat Regression - Regression - Fit regression model - graphs - select four in one or any plot individually
As you read the L
Data Analysis (Week 4) Guide
Omair Khan
February 6, 2016
Introduction
This is a tougher assignment than the one we did last time. This week, we will introduce for loops and their
many uses. We will also create a function that will generate the test MSE ba