Homework 7 - STAT 462, Fall 2015
Please bring a hard copy of your homework to class and submit it at the beginning of the class or
submit it via ANGEL before class. You could either type or write down your answers. Attach your
code used to obtain your res
Homework 4 Solutions
Please bring a hard copy of your homework to class and submit it at the beginning of the class. You may
either type and/or write down your answers. For the questions that require software, please paste your
output under the question o
Stat 462 Exam 2 Key
1a. Key ideas are that each smaller model must be a subset of the larger model and, given that restriction, we look
for smallest SSE.
FORM NOT BB Answer= x1,x2,x3 then x2,x3 then x3
FORM BB Answer= x2,x3,x4 then x2,x3 then x3
1b. SSE(x
Homework 1 Solutions
Please bring a hard copy of your homework to class and submit it at the beginning of the class. You may
either type and/or write down your answers. For the questions that require software, please paste your
output under the question o
Stat 462 Exam 2 Guidelines
Exam is in-class, Wed. Mar. 24
You can use one page (one side) of notes during the exam.
Readings : Chapters 7, 8, 9
Things you should know
Extra sums of squares - Calculation and interpretation of SSR (set 1 of X|set 2 of X)
Fall 2016
Name_
Section_
Stat 462 Exam 1
This is a 50-minute practice exam.
A calculator and one sheet of notes (both sides) are allowed but may NOT be shared with others.
ID_
1. The researchers are interested in relation between handspan and height. They
Introduction of Regression
Simple Linear Regression
Chapter 1: Introduction and Simple Linear
Regression
STAT462 Applied Linear Regression, Chapter 1
Chapter 1: Introduction and Simple Linear Regression
Introduction of Regression
1
Introduction of Regress
Extra Sums of Squares
Partial R 2
General Linear F-test
Multicollinearity
Chapter 5: General Linear F-test Procedure and
Multicollinearity
STAT462 Applied Linear Regression, Chapter 5
Chapter 5: General Linear F-test Procedure and Multicollinearit
Extra S
STAT 462: Applied Regression Analysis
Week 1 Chapter 1 Introduction
Instructor: Matthew Reimherr
1 / 19
Outline
I
Introductory statistical concepts.
2 / 19
Faraway package
The Faraway package in R primarily contains various data sets
from the book, though
Linear Models
with R
Second Edition
CHAPMAN & HALL/CRC
Texts in Statistical Science Series
Series Editors
Francesca Dominici, Harvard School of Public Health, USA
Julian J. Faraway, University of Bath, UK
Martin Tanner, Northwestern University, USA
Jim Zi
STAT 462: Applied Regression Analysis
Week 3 Chapter 2 Estimation
Instructor: Matthew Reimherr
1 / 19
Outline
I
Parameter estimation.
2 / 19
Linear Regression Model
Recall that the model we are dealing with is
Y = 0 + 1 X1 + + p Xp + .
Again, when we writ
Lab Activity 1
Note: You may want to include necessary figures from the output of MINITAB.
Part 1 (30pts) Open the dataset shoes size and height from the ANGEL page. This is the data set we
collected in class.
A. Human heights are usually normally distrib
Lab Activity 2
Please finish this lab activity during the class time and submit in the drop box on Angel.
Please paste/copy any plot and output of Minitab that is used to answer each question.
Part 1: (Driver Age and the Maximum Legibility Distance of Hig
Lab Activity 5
Note: Please include the necessary plot(s) or Minitab output that are used to answer each part of
the following question.
Open the dataset Temperature, which includes geographic latitude, mean January temperature,
mean April temperature, an
Lab Activity 3
Note: Please include the necessary plot(s) or Minitab output that are used to answer
each part of the following question.
Part 1: The director of admissions of a small college selected 120 students at random from
the new freshman class in a
Lab Activity 7
Note: Please include the necessary plot(s) or Minitab output that are used to answer each part of the
following question.
Open the dataset Senic. We have:
Y = InfctRisk, the risk of infection at a hospital
X1 = Stay, average length of stay
Extra Sums of Squares
Partial R 2
General Linear F-test
Multicollinearity
General Linear F-test and Multicollinearity
Lingzhou Xue
Department of Statistics, The Pennsylvania State University
Fall 2016
STAT 462 Applied Linear Regression
Chapter 5: General
Study Guide for Exam 1
STAT 462, Fall 2016
Note:
You are allowed to take one calculator and one sheet (both sides) of formulas and notes
for the exam. However, you cannot share your calculator or notes with others.
The exam will be 50 minutes in class o
Lab Activity 6
Please finish this lab activity during the class time and submit in the drop box on Angel.
Note: Please include the necessary plot(s) or Minitab output that are used to answer each part of the
following question.
The data set PIQ contains d
STAT 462
Fall 2016
Homework #6
Problem 1
1 1
2 1 0
Let = [2 3], = [
], = [1, 2, 0], and = 3 (a scalar). Perform the operations
0 3 3
1 2
below, if possible. If not possible, explain why, and give a simple adjustment that makes it possible.
In this problem
Homework 6 Solutions
STAT 462 Section 2, Fall 2016
Problem 1
I will only show the results here, not the arithmetic steps that produce them.
(a)
#
[,1] [,2]
# [1,]
-3
-5
(b)
#
[,1]
# [1,]
-3
# [2,]
-5
(c)
#
[,1] [,2]
# [1,]
3
1
# [2,]
3
6
# [3,]
1
-1
(d)
N