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 M
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. Th
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 (1
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
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
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
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=3
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
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
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
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:
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]
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
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. Th
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
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 Carolin
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, an
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
Conti
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
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
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 o
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
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
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 relatio
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 cas
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 = cbi
1.
attach(prob0635)
> Group=factor(Group)
> trt1=aov(gplevel~Group)
> anova(trt1)
Analysis of Variance Table
Response: gplevel
Df Sum Sq Mean Sq F value
Pr(>F)
Group
3 917.56 305.853 6.2899 0.001235 *