Stat 401G
Lab 3
Solution
A study was done to see if the body mass of carnivores was related to the bite force the
animal produces. Twenty-five species of carnivore were randomly selected and the body
mass (kg) and bite force (N) was determined for each sp
Stat 401 F/XW
HW 8 sketch answers:
1) Meat pH over 24 hours (2 pt each part)
a) There seems to be lack of fit.
Residuals plot show a clear bend indicating lack of fit.
resid
0.4
0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3
-0.4
5.1
5.2
5.3
5.4
5.5
5.6
5.7
5.8
5.9
6.0
6
04:37 Friday, October 19, 2012 1
Stat 401 F / XW Homework 7 answers
1) Wine and mortality (1 pt each part)
a)
No, a linear regression model is not appropriate. The relationship looks curved.
b) The other three plots are:
04:37 Friday, October 19, 2012 2
L
Stat 401G
Lab 1
Solution
Use JMP to analyze the data in problem 1 below. It is not sufficient to simply hand in
JMP output. You must answer the questions completely. Hand in the JMP output attached
at the end of your written (word processed) solutions.
1.
Stat 401G: Quiz 2 Homework Solutions For Wednesday September 14, 2011 Note: On a quiz and test, I will give you the sample mean and standard deviation. For this homework, let JMP calculate these statistics. In my solutions, I will carry the decimals out f
Stat 401B Final Exam
December 16, 2008
Name: _
INSTRUCTIONS: Read the questions carefully and completely. Answer each question
and show work in the space provided. Partial credit will not be given if work is not
shown. Use the JMP output. It is not necess
Stat 401 B Lecture 1
First Day
Data Sheet fill out and
bring to lab tomorrow
Syllabus go over
1
The Big Picture
What is statistics all about?
2
The Big Picture
Statistics is about variability!
Recognizing
variability.
Quantifying variability.
Explaining v
Stat 401, Sample Final Exam Problems adapted from Dec. 1995
INSTRUCTIONS FOR THE FINAL EXAM
The examination consists of 10 short-answer questions. Choose any 10
questions to answer from the 12 questions given. Each question counts 10
points.
The exam is c
Solutions to HW7, Stat 401 Spring 2011
(1). Ch. 10 #18. Here we have I = 5 groups, consisting of J = 4
observations each, with respective group means and sample variances
i=1
cfw_Xi 5 = (12.75, 17.75, 17.50, 11.50, 10.00)
cfw_Si2 5 = (17.583, 12.917, 4.3
Midterm Bonus Question Solution
Question: Suppose there are 10 rats and 30 pellets. Suppose further that the pellets
are distributed to the rats equiprobably. Find the probability that every rat receives at
least 2 pellets.
Remark: There are many ways to
Solution: Homework 9
(8.2.5)
(a) 1.00 (3.355)(0.24), which equals to (0.19, 1.81) or 0,19 < D < 1,81 lb.
(b) We are 99 % condent that mean weight loss on mCPP is between 0.19 and 1.81 lb greater
than when on placebo.
STAT 371
page. 1
.
STAT 371
page. 2
Solutions to HW3, Stat 401 Spring 2011
Note: since #38(b) on p.277 is a tolerance interval, a topic I said we
skipped, the 5 points for that problem are extra-credit. So the denominator
for this HW is 75 points.
(1). You were asked to exhibit CIs for 100
Solutions to HW4, Stat 401 Spring 2011
(1). #10, pp. 293-4. (a). H0 : = 1300, HA : > 1300. (b).
Under H0 , X N (1300, 602 /20), and type I error probability =
1 (1331.26 1300)/(60/ 20) = .010. (c). When = 1350, llX
2
N (1350, 60 /20), and the probability
Stat 401 B Lecture 11
Multiple Regression
A single numerical response
variable, Y.
Multiple numerical explanatory
variables, X1, X2, Xk
1
Simple Linear Regression
Y = y| x +
Y = 0 + 1 x +
2
3
Stat 401 B Lecture 11
Multiple Regression
Y = Y | x1 , x2 ,.
Stat 401 B Lecture 24
Model Selection
In multiple regression we
often have many explanatory
variables.
How do we find the best
model?
1
Model Selection
How can we select the set of
explanatory variables that will
explain the most variation in the
respons
Stat 401 B Lecture 8
Regression model
Y = y| x +
Y
represents a value of the response
variable.
y| x represents the population mean
response for a given value of the
explanatory variable, x.
represents the random error
1
Linear Regression Model
Y = y|
Stat 401 B Lecture 5
Two Independent Samples
Question
In
2000, did men and
women differ in terms of
their body mass index?
1
Populations
random
selection
2. Male
Inference
1. Female
random
selection
Samples
2
Body Mass Index
Females
Males
n1 = 50
n2 = 50
Stat 401B Exam 2
November 4, 2008
Name: _
INSTRUCTIONS: Read the questions carefully and completely. Answer each question
and show work in the space provided. Partial credit will not be given if work is not
shown. Use the JMP output. It is not necessary t
Stat 401B Exam 1
September 30, 2008
Name: _
INSTRUCTIONS: Read the questions carefully and completely. Answer each question
and show work in the space provided. Partial credit will not be given if work is not
shown. Use the JMP output. It is not necessary
Stat 401 B Lecture 23
Home Gas Consumption
Interaction?
Should there be a different
slope for the relationship
between Gas and Temp after
insulation than before
insulation?
1
Home gas consumption
Create a new explanatory
variable.
Temp*Insul
This will
Stat 401 B Lecture 22
Multiple Regression
Response, Y (numerical)
Explanatory variables, X1, X2,
Xk (numerical)
New explanatory variables
can be created from existing
explanatory variables.
1
Home gas consumption
Weekly gas consumption for a
home in Eng
Stat 401 B Lecture 17
Prices of Antique Clocks
Antique clocks are sold at
auction. We wish to investigate
the relationship between the age
of the clock and the auction
price and whether that
relationship changes if there are
different numbers of bidders a
Stat 401 B Lecture 7
Simple Linear Regression
Question
Is
annual carbon dioxide
concentration related to
annual global temperature?
1
Bivariate Fit of Temp By CO2
15.0
Temp
14.5
14.0
13.5
300
350
400
CO2
Linear Fit
2
Linear Fit
y = 0 + 1 x
Predicted Tempe
Stat 401 B Lecture 27
Model Selection
Response: Highway MPG
Explanatory: 13 explanatory
variables
Indicator variables for types of car
Sports Car, SUV, Wagon, Minivan
There is an indicator for Pickup but
there are no pickups in the data.
1
Indicator Va
Stat 401 B Lecture 6
Simple Linear Regression
Question
Is
annual carbon dioxide
concentration related to
annual global temperature?
1
Simple Linear Regression
Response variable, Y.
Annual
(o
global temperature
C).
Explanatory (predictor)
variable, x.
An
Stat 401 B Lecture 3
Parameter numerical
summary of the entire
population.
Population all items
of interest.
Example: All vehicles made
In 2004.
Example: population mean
fuel economy (MPG).
Sample a
few items from
the population.
Example: 36
vehicles.
Sta