MA416
Assignment 2
Simple Linear Regression
SOLUTION
The following are Age and Systolic Blood Pressure (SBP) data taken from 4 participants
of the Framingham Heart Study. Assume the underlying relatio
MA416
Assignment 1
Simple Linear Regression
SOLUTION
The following are Age and Systolic Blood Pressure (SBP) data taken from 4 participants of the Framingham
Heart Study. Assume the underlying relatio
MA416 Exam 1
SOLUTION
Name: _
Thursday, Oct 15, 2015
Discussion Day and Time: _
There are 2 problems for this exam (each with multiple parts). The test is based on 100 points. There are 3 pages to the
MA416
Assignment 7
Qualitative Regression with Interaction: >2 Groups
SOLUTION
Take the data from Problem 22.7 and combine with the data from the three groups in Problem 16.7, as stated in
problem 22.
MA416
Assignment 6
Two-group Qualitative Regression/Interaction
SOLUTION
1. Problem 16.7 on Page 723 as follows, using linear regression techniques: PLEASE COMPLETE THIS
PROBLEM MANUALLY (NOT SAS)
i.
MA416
Assignment 4
Simple Linear Regression using SAS
SOLUTION
NOTE: Please do all of this assignment in SAS. Please print your SAS output and specifically point out the
answer to each question on the
MA416
Assignment 3
Simple Linear Regression
SOLUTION
NOTE: FOR THIS AND ALL ASSIGNMENTS IN THE FUTURE, PLEASE HAND IN
YOUR HOMEWORK ON 8.5-X-11 PAPER. PLEASE MAKE SURE YOUR NAME
AND THE DAY OF YOUR DI
MA416
Assignment 5
Multiple Linear Regression Using SAS
SOLUTION
The following is the data to be used for this assignment:
4264
4496
4317
4292
4945
4325
4110
4111
4161
4560
4401
4251
4222
4063
4343
48
MA416
Assignment 3
Simple Linear Regr ession
DUE: Thur sday, September 29, 2016, in class.
NOTE: FOR THIS AND ALL ASSIGNMENTS IN THE FUTURE, PLEASE HAND IN
YOUR HOMEWORK ON 8.5-X-11 PAPER. PLEASE MAKE
MA416
Assignment 1
Simple Linear Regression
Due Tuesday Sept 13 in Class
NOTE: FOR THIS AND ALL ASSIGNMENTS IN THE FUTURE, PLEASE HAND IN
YOUR HOMEWORK ON 8.5-X-11 PAPER. PLEASE MAKE SURE YOUR NAME
AN
ods html close;
ods html;
ods rtf file='c:\courses\courses\ma416\MultReg.rtf';
options nodate nonumber nocenter;
title1 'Multiple Regression of College GPA vs. Independent Variables';
data new;
input
MA416
Assignment 6
Two-gr oup Qualitative Regr ession/Inter action
THIS HOMEWORK DOES NOT NEED TO BE HANDED IN
(A solution will be provided in a few days)
PLEASE USE SAS FOR ALL PROBLEMS BELOW:
1. Pag
MA416
Assignment 4
Multiple Linear Regr ession using SAS
Due Thur sday, October 6, 2016 in Class
(PLEASE REMEMBER TO PUT YOUR NAME AND DISCUSSION
SECTION DAY ON YOUR HOMEWORK)
Please answer questions
MA416
Assignment 7
Qualitative Regr ession with Inter action: >2 Gr oups
Due in class on November 3, 2016
Take the data from Problem 22.7 and combine with the data from the three groups in Problem 16.
Example of Simple Linear Regression in SAS
SAS PROGRAM:
options nodate nonumber nocenter;
data joe;
input age numb_attempts;
datalines;
20 5
55 12
30 10
50 11
25 6
40 .
run;
proc reg data=joe;
title1
MA416
Assignment 5
Two-gr oup Qualitative Regr ession
Due in class on Thursday, October 13
1. Problem 16.7 on Page 723 as follows, using linear regression techniques: PLEASE COMPLETE THIS
PROBLEM MANU
MA416
Assignment 2
Simple Linear Regression
Due Thursday Sept 22 in Class
NOTE: FOR THIS AND ALL ASSIGNMENTS IN THE FUTURE, PLEASE HAND IN
YOUR HOMEWORK ON 8.5-X-11 PAPER. PLEASE MAKE SURE YOUR NAME
A
MA416
Assignment 8
Single-Factor Studies: ANOVA Approach with Pairwise Comparisons and Contrasts
Due in class on November 10, 2016
Please do the following problems using SAS PROC GLM unless otherwise
MA416
Assignment 6
Two-gr oup Qualitative Regr ession/Inter action
Due Thursday October 26, in class
Please place the final answers in the order that they are asked,
cutting and pasting the relevant S
MA416
Assignment 4
Multiple Linear Regr ession using SAS
Due Thur sday, October 5, 2017 in Class
(PLEASE REMEMBER TO PUT YOUR NAME AND DISCUSSION
SECTION DAY ON YOUR HOMEWORK)
Please place the final a
MA416
Assignment 3
Simple Linear Regression
SOLUTION
NOTE: FOR THIS AND ALL ASSIGNMENTS IN THE FUTURE, PLEASE HAND IN
YOUR HOMEWORK ON 8.5-X-11 PAPER. PLEASE MAKE SURE YOUR NAME
AND THE DAY OF YOUR DI
MA416
Assignment 1
Simple Linear Regression
Due Tuesday Sept 12 in Class
NOTE: FOR THIS AND ALL ASSIGNMENTS IN THE FUTURE, PLEASE HAND IN
YOUR HOMEWORK ON 8.5-X-11 PAPER. PLEASE MAKE SURE YOUR NAME
AN
MA416
Assignment 3
Simple Linear Regr ession
DUE: Thur sday, September 28, 2016, in class.
NOTE: FOR THIS AND ALL ASSIGNMENTS IN THE FUTURE, PLEASE HAND IN
YOUR HOMEWORK ON 8.5-X-11 PAPER. PLEASE MAKE
MA416
Assignment 1
Simple Linear Regression
Due Tuesday Sept 12 in Class
NOTE: FOR THIS AND ALL ASSIGNMENTS IN THE FUTURE, PLEASE HAND IN
YOUR HOMEWORK ON 8.5-X-11 PAPER. PLEASE MAKE SURE YOUR NAME
AN
Assignment 7
a. Let Y=Productivity;
X1=1 if it is from low group, if no X1=0;
X2=2 if it is from moderate group, if no X2=0;
X3=prior years productivity
Y= b0 + b1X1 + b2X2 + b3X3 + b4X1*X3 + b4X2*X3
a.
X3 is correlated with y since its p<.0001, meaning that there is enough evidence that correlation
coefficient between x3 and y is not 0.
X3 seems to be correlated with x1 since p = .0821, meaning t
2.
b.
y = 38.00 14.00x
c.
sum of residuals = 0
d.
showed in part b
e.
Ho: 1= 2
Ha: 12
According to SAS t = -5.12(p=0.0003), so we can reject the null hypothesis in 99% confidence
level
Using code -1
MA 684 Class 7
More on Interaction variables and Centering
Stepwise Regression
Interaction models
Example: FHS, systolic blood pressure
Main effect model:
Differences between males, females?
Effect of
MA 684 Class 6
Categorical Predictors
Interaction variables
Voting Survey: Factors associated with political
awareness
Creating dummy variables in R
The ifelse( ) command
Example: party categorized as
Simple Regression in SPSS
Example: Predicting sleeptime from age for a sample of 13 children
Summary statistics, means and standard deviations
Analyze Descriptive Statistics Descriptives
Descriptive S
Simple Regression in SAS
Example (predicting sleep time (ATST is average total sleep time for a day) from age (in years):
data kids;
infile 'C:\Users\tch\Documents\1. Classes\ma684\Data Sets\kkc5p6.tx
MA684 Class 10
Logistic Regression II
Logistic regression
Example: are at least one of age, sex, race, car age,
and vision problem related to probability of car crash?
DEPENDENT: Crash: 1=Yes, 0=No