Formula sheet for the MLR Minitab output
Model: y 0 1 x1 2 x2 3 x3
Estimated regression equation
, where p = # of Xs = 3
y b0 b1 x1 b2 x2 b3 x3
The individual t test for each i .
Predictor
Coef
SE Coef
T
Constant(intercept) b0
SE(b0)= sb 0
X1
b1
SE(b1)=
Chapter 14.4 Model Assumption
Review what we learned.
The simple linear regression model
y 0 1 x
(1)
Model Assumptions
1. The error term is random variable, E ( ) 0, Var ( ) 2 .
Explain:
2. The variance of , denoted by 2 , is the same for all values of t
Stat 351 Homework #2
(Total points is 10) from chapter 14.
Due date: TBN
Problem 3 (part a, b, c) from chapter 14.
Requirements and information:
1). For Problem 3 part a, use Minitab to produce your plot, then copy
and paste it to a word document. (Data n
Stat 351 Homework #4
(Total points is 10)
Due date: 02/25/15 on Thursday
Problem 1: The data is in this table: (Calculation by hand, not Minitab)
xi
yi
1
3
2
7
3
5
4
11
5
14
(a) Get the estimated regression equation by hand calculation.
(b) Develop a 95%
Stat 351 Homework #3
(Total points is 10)
Due date: TBN
Problem 1:
The following information regarding a dependent variable (Y) and an
independent variable (X) is provided.
Y
X
4
2
3
1
4
4
6
3
8
5
1). Compute SSE,SSR and SST by hand
2). Compute coefficien
1
Taelor Flemons
Xiongya Li
STAT 351
7 September 2016
Homework 1
1. Playbill magazine reported that the mean annual household income of its readers is
$199,155 (playbill, January 2006). Assume this estimate of the mean annual household
income is based on
Practice Financial Statement Analysis Problems
1. Given the following data for a company, what is their ROA?
Sales = $30 million
Total debt = $5 million
ROE = 10%
Profit margin = 5%
A. 2.5%
B. 5%
C. 7.5%
D. 10%
E. 15%
2. Given the following data for a com
Stat 351 Homework #1
Due date: Thursday (Jan. 28th) at the beginning of the class.
You will lose credit if you dont show your work.
1. Playbill magazine reported that the mean annual household income of its readers
is $199,155 (playbill, January 2006). As
Stat 351 Homework #3
Due date: Friday (10/12) at by the end of the class.
Make sure to show your work if you did any calculation, and minitab output if you used minitab.
1.
Problem 47 on Page 652. Please download the dataset named FourSeasonRestaurant fro
Stat 351 Homework #9. Chapter 17
Due date: TBN
1: exercices 19. a, b, c.
Requirement:
Part(a): use Minitab to get the plot.
Part (b) and (c): Do hand calculations. Do not use Minitab. Show your calculations and
calculation table.
Notes:
1. Show all works
Stat 351 Homework #8. Chapter 17
Due date: TBN
1: exercices 8. a, b, c.
Requirement: Do hand calculations. Show your calculations and then put the results in
the table.
Week
1
2
3
4
5
6
7
8
9
10
11
12
TimeSeries WeightedMoving
Value
AverageForecast
17
21
Stat 351
Homework #6. Chapter 16.1
Due TBN
Problem 1: Exercise 3 in Chapter 16, part a-d.
Problem 2:
a). What is the form of the general linear model? The linear model is called linear in
terms of what parameters?
b). In the general linear model, where z
Stat 351 Section B Homework #7
Due date: TBN
Problem 1: Chapter 16 exercise 10
Problem 2: Chapter 16 exercise 11
Problem 3: Chapter 16 exercise 16
Note: Data name Layoffs in the data folder.
Stat 351Homework #5
(Total points is 10)
Due date: TBN
Problem 1: Chapter 15 exercise 34, part a-c.
Problem 2: Chapter 15 exercise 37, part a-f
Note:
Use the Homework5Restaurant data, answer the questions
and show minitab output if needed.
Problem 3: Chap
RestaurantType
Price ($) Score
Bertucci's Italian
16
Black AnguSeafood/St
24
Bonefish GrSeafood/St
26
Bravo! CuciItalian
18
Buca di Be Italian
17
Bugaboo CrSeafood/St
18
Carrabba's Italian
I
23
Charlie Br Seafood/St
17
Il Fornaio Italian
28
Joe's Crab Sea
Homework #4
Problem 1:
The estimated regression equation is
y 0.2 2.6 x
b.
y 0.2 2.6 x 0.2 2.6(4) 10.6
y p t / 2 s y p
10.63.182(1.11)=10.63.53
or7.07to14.13
d.
y p t / 2 sind
10.63.182(2.32)=10.67.38
or3.22to17.98
Problem 2:
a. Scatter diagram:
b.
There
Stat 351 Homework #3
Problem 1: The following information regarding a dependent variable (Y) and an
independent variable (X) is provided.
Y
X
4
2
3
1
4
4
6
3
8
5
1). Compute SSE,SSR and SST by hand
2). Compute coefficient of determination (r2)
1) You firs
Stat 351 Homework #2
(Total points is 10) from chapter 14.
Problem 3 (part a, b, c) from chapter 14.
Requirements and information:
1). For Problem 3part a, use Minitab to produce your plot, then copy and paste it to a
word document. (Data need to be typed
Stat 351 Homework #1
(Total points is 10)
1. The F ratio in a completely randomized ANOVA is the ratio of
a.
b.
c.
d.
MSTR/MSE
MST/MSE
MSE/MSTR
MSE/MST
2.The critical F value with 6 numerator and 60 denominator degrees of freedom at = .05 is
a.
b.
c.
d.
3
Stat 351 Homework #2
Due date: Wednesday (9/21) by the end of class.
You will lose credit if you dont show your work.
1. Problem 2 on Page 608. Use the dataset and answer the following questions.
a) Develop a scatter diagram for these data.
b) What does t
Stat 351 Homework #1
Due date: Wednesday (9/7/16) by the end of class.
You will lose credit if you dont show your work.
1. Playbill magazine reported that the mean annual household income of its readers
is $199,155 (playbill, January 2006). Assume this es
x ix
Pop SD = =
)2 N
Pop variance = 2
x ix
Sample SD = s =
)2 n -1
Confidence Interval
Known = x
za/2 (
n )
Unknown = = x
ta/2 ( s
n )
Hypothesis Testing
1. Develop the null & alt. hypotheses
2. Level of significance
3. Compute test statistic
4. Dra
Chapter 15 Multiple Linear Regression
15.1 &2. The model and LS method
Review the simple linear regression:
Model:
Regression equation:
Estimated regression equation:
1
Parameters:
Estimates:
Hypotheses testing:
2
The estimated regression equation
y b0 b1
Chapter 14.8 Residual Analysis
Review what we learned.
The model assumptions:
Residual analysis:
Example:
Table 1. The residuals for Amand's pizza Parlors.
(1)
(2)
(3)
Student
Quarterly Sales Estimated
Population(1000s)
($1000s)
sales
y i 60 5 xi
= xi
= y
Chapter 14.6 Estimation and prediction
Review what we learned
Purpose
1
Example 1: The least square estimated regression equation for the Armand's
pizza polar example is y 60 5 x , what is the point estimate of the mean
quarterly sales for all restaurants
Formula sheet for the SLR Minitab output
The model:
y 0 1 x
Estimated regression equation
y b0 b1 x
Predictor
Coef
SE Coef
T
Constant(intercept) b0
SE(b0)= sb 0
b1
SE(b1)= sb
P
x
s MSE
1
t stat1
b1
sb1
P-value for 1
SSR
SSE
R2
SST
n2 ,
General form of
Chapter 14.2 and 14.3 Least Squares Method and
Coefficient of Determination
Purpose:
Example 1. The random sample for 10 Armand's Pizza Parlors.
Restaurant Student
Sales
Population Quarterly
($1000s)
(1000s)
i
xi
yi
1
2
58
2
6
105
3
8
88
4
8
118
5
12
117
Stat 351 Review
1. Population
Sample
Example 1: The 2000 U.S. census tried to gather basic information from
every household in the United States. In addition, a longer form was sent to
a sample about 17% of the households asking for more detailed informat