Spring 2010 STA 4322 Intro. Statistics Theory (Sec. 7474) STA 5328 Fnd. Statistical Theory (Sec. 7482) Tuesday 4, Thursday 4/5 @ Griffin/Floyd 100
Instructor: Dr. Larry Winner Office: 228 Griffin/Floyd E-mail: [email protected] Phone: (352) 273-2995 Web
STA 4322/5328 Spr/2010 Major Exam1
PRINT NAME _
)
For all problems, the sample mean, sample variance, and sample proportion are:
^ 2 1n 1n Y Yi Sample variance : Yi Y Sample Proportion : p = where Y ~ Bin(n, p ) n i =1 n-1 i =1 n Q.1: Suppose Y1,Yn denote
STA 4322/5328 Spr/2010 Mini Exam1
PRINT NAME _
)
For all problems, the sample mean, sample variance, and sample proportion are:
^ 2 1n 1n Y Yi Sample variance : Yi Y Sample Proportion : p = where Y ~ Bin(n, p ) n i =1 n-1 i =1 n Q.1: A spectrometer gives
STA 4322/5328 Spr/2010 Mini Exam1
PRINT NAME _
)
For all problems, the sample mean, sample variance, and sample proportion are:
^ 2 1n 1n Y Yi Sample variance : Yi Y Sample Proportion : p = where Y ~ Bin(n, p ) n i =1 n-1 i =1 n Q.1: A spectrometer gives
STA 4322/5328 Spring 2010 Project 4 Due 4/20/10 Likelihood Ratio Tests and Wald Tests
A large metropolitan school district is considering a long-term contract with a light bulb manufacturer. Two companies have placed bids, and the school district wishes t
STA 4322/5328 Spring 2010 Project 3 Due 3/30/10 Odds Ratios
John Snow conducted a census of London residents in the 1850s during a cholera epidemic to try and determine how the epidemic was spread (airborne, waterborne, etc). He obtained the following con
STA 4322/5328 Project 2 Spring 2010 Due Tuesday March 2
Part 1: Acidity Levels in a Lake A biologist is interested in the acidity levels in a lake. The levels vary along a normal distribution with a mean of 6.0 and a variance of 0.16 (which she is not awa
STA 4322/5328 Project 1 Spring 2010 Due Thursday Feb. 4
Part 1: Customers arriving at a Restaurant
The number of customers arriving at Cow-Fil-A between 11:30 and 1:30 on weekdays follows a Poisson distribution with mean =25 per 10 minute period. The mana
Odds Ratios
Suppose we have 2 independent random samples from Bernoulli Distributions: X 1 ,., X m ~ Bernoulli ( p X ) Y1 ,., Yn ~ Bernoulli ( pY )
We wish to estimate pX and pY by maximum likelihood (as well as some functions of them):
x m x L( x1 ,., xm