Stat 372 Term Test I (F12) Solutions
1) Based on observations taken over a given period, a process with specification limits 5.0 2.8 has capability
ratio Ppk = .55.
a) [3] Suppose the sample mean is 4.5. What is the estimate of the process standard deviat
Solutions to selected problems in
Brockwell and Davis
Anna Carlsund
Henrik Hult
Spring 2003
This document contains solutions to selected problems in
Peter J. Brockwell and Richard A. Davis, Introduction to Time Series and Forecasting, 2nd Edition, Springe
Stat 372: Statistics for Business II (Spring 2014)
Assignment #1
Due date: Thursday, June 12 in class
(Print):
,
(Last name)
(First name)
UW Student ID Number:
1
STAT 372: Assignment 1
(Spring 2014)
This assignment is due in class on Thursday June 12th. F
Stat 372: Statistics for Business II (Spring 2014)
Assignment #3
Due date: Tuesday, July 29 in class
(Print):
,
(Last name)
(First name)
UW Student ID Number:
1
STAT 372: Assignment #3
(Spring 2014)
This assignment is due in class on Tuesday July 29. For
# Assigning a number to the variable x
> x <- 3
>x
[1] 3
# adding a value to x (notice that the value of x does not change)
> x+4
[1] 7
# another way of assigning a value to x
> x=3
>x
[1] 3
# boolean operator to check if x is equal to something
> x=3
[1]
R Reference Card
by Tom Short, EPRI PEAC, tshort@epri-peac.com 2004-11-07
Granted to the public domain. See www.Rpad.org for the source and latest
version. Includes material from R for Beginners by Emmanuel Paradis (with
permission).
Getting help
Most R f
> y <- read.table('E:\R\Data.txt',header=T) #importing the data into R
>y
accidents
1
4
2
12
3
3
4
8
5
2
.
.
.
> accidents # notice that if you don't run the command attach, the variable accidents is not recognized.
Error: object 'accidents' not found
> a
STAT 372: Statistics for Business II
SPRING 2014
This course is about statistical thinking and process improvement via statistical methods, forecasting and experimental designs. We will discuss the fundumentals of statistical process control and how a pro
Stat 372: Statistics for Business II (Winter 2013)
Assignment #2
Due date: Thursday, July 10 in class
(Print):
,
(Last name)
(First name)
UW Student ID Number:
1
STAT 372: Assignment #2
(Spring 2014)
This assignment is due in class on Thursday July 10. Fo
Stat 372 (F15) - Assignment #4:
(Due: Fri, Dec. 4 at noon (12:00 pm) to Karen Richardson in M3 3114. Note that the office may be closed for
lunch from 12:00 - 1:00. Electronic submissions or in-class submissions will not be accepted under any
circumstance
Stat 372 (F15) - Assignment #2:
(Due: Fri, Oct. 30 at noon (12:00 pm) to Karen Richardson in M3 3138. Note that the office may be closed for
lunch from 12:00 - 1:00. Electronic submissions or in-class submissions will not be accepted under any
circumstanc
Stat 372 (F15) - Assignment #1:
(Due: Tues, Oct. 13 at noon (12:00 pm) to Karen Richardson in M3 3138. Note that the office may be closed for
lunch from 12:00 - 1:00. Electronic submissions or in-class submissions will not be accepted under any
circumstan
Launching Eikon
To launch Eikon, type Eikon in the Start Menu search bar. Selecting Thomson Reuters
Eikon will open the main Eikon application, while selecting Thomson Reuters Eikon Microsoft Excel will open the version of Excel that can access the Eikon
F15 course outline
STAT 372 Survey Sampling and Experimental Design for Business
University of Waterloo
Instructor:
Peter Balka
M3 2007 x35546
pbalka@uwaterloo.ca
Office hrs. posted weekly on door and on course website.
Class Times and Location: Lecture:
University of Waterloo
Stat 372 W15
Midterm
Date: Thursday, March 5. Duration: 80 minutes
Family Name: First Name: ID. #2
Signature:
Instructor: P. B'alka _[
50 he / (9 719
Instructions:
0 This exam has 8 pages including this cover page. The marks for eac
STAT 372: Assignment #2 - Spring 2014
(solutions: total = 45 marks)
1 Concepts and Theory
1. The CUSUM chart is, traditionally, for detecting a persistent shift in the mean of
the process. Suppose we are interested in developing a similar chart for detect
data<-read.table(file.choose(),header=T)
attach(data)
rowmean=apply(data,1,mean)
columnmean=apply(data,2,mean)
rowmean
cloumnmean
overallmean=mean(rowmean)
overallmean
ss_treat=10*sum(columnmean-overallmean)^2)
#columnmean-overallmean produce a a set cont