STA 6167 Course Information Spring 2006
Instructor: Office: Telephone: e-mail Office Hours: Grad. TA Office: Telephone: Email Office Hours: Class Time: Class Room: Text: Topics:
Ramon C. Littell 404 McCarty C 392-3040 [email protected] 9:00-11:00 Wednesday
Logistic, Poisson, and Nonlinear Regression Problems
Logistic Regression
QA.1. A study is conducted to measure the effects of levels of a herbicide on the probability of death for 2
weed varieties. The researcher selects 5 dosage levels, and assigns each
STA 6167 Exam 3 Spring 2014 PRINT Name _
Conduct all tests at = 0.05 significance level.
Q.1. Three Poisson regression models relating the rate of fatalities for the British rail system versus year (1967-2003)
were fit. The rate was (fatalities/million mi
STA 6167 Exam 1 Spring 2014 PRINT Name _
For all significance tests, use = 0.05 significance level.
Q.1. A simple linear regression was fit relating number of species of arctic flora observed (Y) and July mean temperature
(X, in Celsius). The results of t
Experimental Design Problems
1-Way ANOVA (Completelely Randomized Design)
QA.1. An experiment was conducted as a Completely Randomized Design (1-Way ANOVA) to compare t = 4 methods of packaging
steaks, in terms of the amount of bacteria measured after 9 d
STA 6167 Exam 2 Spring 2013
PRINT Name _
Note: Conduct all individual tests at =0.05 significance level, and all multiple
comparisons at an experiment-wise error rate of E = 0.05.
Q.1. An experiment was conducted to determine the effects of viewing a mag
STA 6167 Exam I Spring 2008
For all problems, use =0.05
A multiple regression model is fit relating a response Y to 6 predictors: X1, X2, X3, X4, X5,
X6. We fit 2 models (each based on a sample of n=34 cases):
i ) E[Y ] 0 1 X 1 2 X 2 3 X 3 4 X 4 5 X 5 6 X
Experimental Design Problems
1-Way ANOVA (Completelely Randomized Design)
QA.1. An experiment was conducted as a Completely Randomized Design (1-Way ANOVA) to compare t = 4 methods of packaging
steaks, in terms of the amount of bacteria measured after 9 d
STA 6167 Exam 2 Spring 2012
PRINT Name _
Note: Conduct all individual tests at =0.05 significance level, and all multiple
comparisons at an experiment-wise error rate of E = 0.05.
Q.1. An experiment is conducted to compare 4 varieties of cheddar cheese (
Exam 2 Topics Spring 2016
Bring the following 3 Tables: t/chi-square/F, Bonferroni, Studentized range
Experimental Design and the Analysis of Variance
1-Way ANOVA - Completely Randomized Design
o Sums of Squares, degrees of freedom, F-test
o Tukey/Bonferr
STA 6167 Exam 1 Fall 2014 PRINT Name _
For all significance tests, use = 0.05 significance level.
Q.1. A study was conducted, relating Total Medical Waste (Y, in kg/day) to hospital type (Government: X1=1, Education and NonEducation: X2=1, University: X3=
STA 6167 Section 1F80
Statistical Methods in research ii
Spring 2016
Tu 2-3, th 3 @ Griffin/Floyd 100
Instructor: Dr. Larry Winner
Office: 228 Griffin/Floyd
Phone: 273-2995
E-Mail: [email protected] (not to be used for technical explanations)
Office Hou
STA 6167 Exam 2 Spring 2011
PRINT Name _
Note: Conduct all individual tests at =0.05 significance level, and all multiple
comparisons at an experiment-wise error rate of E = 0.05.
Q.1. An experiment is conducted to determine the effects of 3 ripening sta
Logistic, Poisson, and Nonlinear Regression Problems
Logistic Regression
QA.1. A study is conducted to measure the effects of levels of a herbicide on the probability of death for 2
weed varieties. The researcher selects 5 dosage levels, and assigns each
Linear Regression Problems
Q.1. A multiple regression model is fit relating a response Y to 4 predictors: X1, X2, X3, X4. We fit
2 models (each based on a sample of n=20 cases):
i) E[Y ] 0 1 X 1 2 X 2 3 X 3 4 X 4
ii ) E[Y ] 0 1 X 1 2 X 2
For model i), the
STA 6167 Exam 3 Spring 2012 PRINT Name _
Conduct all tests at = 0.05 significance level.
Q.1. A study was conducted to relate incidence of West Nile virus in horses among the counties of South Carolina. The dependent
variable was the number of cases of We
STA 6167 Exam 1 Spring 2011 PRINT Name _
Part 1: Degrees of Freedom in the Analysis of Variance
Q.1. A linear regression model is fit, relating breaking strength of steel bars to thickness, length, and material
type with 3 nominal levels (no interaction t
STA 6167 Exam 3 Spring 2013 PRINT Name _
Conduct all tests at = 0.05 significance level.
Q.1. A study was conducted to compare Y=Average Daily Weight Gain (Kg) under 2 Grazing Conditions (Z=1 if
Continuous, 0 if Rotated), adjusting for a Covariate X = Sto
STA 6167 Spring 2011 Exam 3 PRINT Name _
Conduct all tests at = 0.05 significance level.
Q.1. A study considered the relationship between number of matings (Y) and age (X) among n=41 African elephants. The
researchers considered 3 Poisson Regression model
STA 6167 Exam 2 Spring 2009
PRINT Name _
Part 1. A study was conducted to measure the effects of age and motorcycle riding on the
incidence of erectile dysfunction (ED). Men were classified by age (20-29,30-39,4049,and 50-59), where the midpoints (25,35,4
STA 6167 Exam 3 Spring 2015 PRINT Name _
Conduct all tests at = 0.05 significance level.
Q.1. A series of Poisson Regression models were fit to relate number of new products developed (Y), to 3 sets of predictor variables.
Control Variables included were:
Linear Regression Problems
Q.1. A multiple regression model is fit relating a response Y to 4 predictors: X1, X2, X3, X4. We fit
2 models (each based on a sample of n=20 cases):
i ) E[Y ] 0 1 X 1 2 X 2 3 X 3 4 X 4
ii ) E[Y ] 0 1 X 1 2 X 2
For model i), th
STA 6167 Exam 1 Spring 2013 PRINT Name _
For all significance tests, use = 0.05 significance level.
Q.1. A study is conducted to compare r = 4 styles on comfort ratings for truck drivers on long trips. A sample of 40 truck
drivers is obtained, and randoml
STA 6167 Exam 2 Spring 2008 PRINT Name _
A study is conducted to measure the relationship between breaking strength of concrete (Y) and
the amounts of 2 key ingredients: A (X1) and B (X2). The relationship is believed to be nonlinear,
and of the form:
. T
1. Fit the crab data into a Poisson Regression
2. See if there overdispersion
We saw that the output is larger than one, but still unsure, we fit the negative binomial
model just in case.
Quiz 6
Mohit Israni
UFID 4338 4979
(a)
The logistic model can be fit as below:
> tumor.logit=glm(cbind(Present,Absent)~Amount,family=binomial(link=logit)
> summary(tumor.logit)
Call:
glm(formula = cbind(Present, Absent) ~ Amount, family = binomial(link =
Quiz 5
View the data at https:/openmv.net/info/travel-timesLinks to an external site.
a.
b.
Use "Fuel Economy" as the response and fit an adequate regression model with only significant predictors. You can ignore "Start Time" from the data. Note there are
Quiz 4
1. For the wool fiber example (Links to an external site.)Links to an external site. we found that
the trt:rev interaction is significant. Create 95% Tukey pairwise comparisons for comparing
a. Different revs within same treatment
b. Different trt
QUIZ 2
Mohit Israni (43384979)
1.
Model :
= + + + +
~(0, 2 )
= 1 4
= 1 4
= 1 4
Blend is the treatment
And Driving Mechanisms and CarModels are Blocks
The problem is solved using Latin Square Design
2.
The data is created as follows:
latin=function (
Quiz 3
Mohit Israni
4338 4979
(a)
The data is of Nested Design
Since every instructor comes in only one of the cities (it is also Balanced Nested design)
We note that instructors are nested within Cities design of form
= + + () +
> xtabs(~city+instructo