Table of Contents

Preface / iv
Keywords Index / vi
Chapter 1 / Introduction and Data Collection / 1
Chapter 2 / Presenting Data in Tables and Charts / 31
Chapter 3 / Numerical Descriptive Measures / 76
Chapter 4 / Basic Probability / 105
Chapter 5 / Some Important Discrete Probability Distributions / 139
Chapter 6 / The Normal Distribution and Other Continuous Distributions / 173
Chapter 7 / Sampling and Sampling Distributions / 210
Chapter 8 / Confidence Interval Estimation / 246
Chapter 9 / Fundamentals of Hypothesis Testing: One-Sample Tests / 286
Chapter 10 / Two-Sample Tests / 327
Chapter 11 / Analysis of Variance / 376
Chapter 12 / Chi-Square Tests and Nonparametric Tests / 417
Chapter 13 / Simple Linear Regression / 467
Chapter 14 / Introduction to Multiple Regression / 518
Chapter 15 / Multiple Regression Model Building / 587
Chapter 16 / Time-Series Analysis and Index Numbers / 615
Chapter 17 / Decision Making / 667
Chapter 18 / Statistical Applications in Quality Management / 699
Chapter 19 / Data Analysis Overview / 733


Preface

The Test Item File contains a variety of multiple-choice, true-false, problem and fill-in questions based on the definitions, concepts, and ideas developed in each chapter. In addition, numerical problems and Microsoft Excel computer output problems are also given with solutions provided in multiple-choice, true-false, problem and fill-in format.

The Test Item File is intended to assist instructors in preparing examinations. The questions included herein highlight the key topics covered throughout each chapter. Keywords are available after each question to help instructors locate questions on a specific topic or concept. Explanation is provided when the rationale of the correct answer to a difficult question is rather obscure. The format for the Test Item File will facilitate grading and should be helpful to instructors who teach very large sections.

The intended difficulty level (easy, moderate, difficult) of each question in the Test Item File is stated in order to facilitate test item selection by instructors wishing to create specific types of exams. However, some words of caution must be given. The classification of question difficulty level is very subjective and each question should be evaluated based on the emphasis the particular topic was given in class and how much emphasis is to be given to numerical results obtained by calculator rather than computerized results obtained from Microsoft Excel. As an operational definition that is used here, items are classified as easy if they pertain directly to definitions and fundamental concepts. Test items are classified as moderate if they require some numerical calculations with more than a minimal number of steps or if they require a broader understanding of the topic. Test items that are classified as difficult are done so because of the level of rigor of the subject, the length of the narrative, the amount of effort required for solution, or for responses that require more thought and analysis.

Instructors are also advised that all answers in the Test Item File are computed using Microsoft Excel or PHStat with no rounding involved in the intermediate steps. If students use rounding with formulae and a calculator, their answers might be different from those provided in the answer keys. Likewise, if students use the statistical tables at the end of the book instead of Microsoft Excel or PHStat, their answers might also differ from those provided in the answer keys due to rounding. Whenever possible, we provide answers obtained using both Microsoft Excel/PHStat and the statistical tables if they are different.

This Test Item File and others that are similar suffer from one major weakness. They do not permit an evaluation of the students’ written communication skill. The authors highly recommend that, if possible, instructors who use this Test Item File supplement it with at least one short essay type question so that an assessment can be made of the students’ understanding of concepts as well as how they can make connections across various topics.

The following tabular display is a breakdown of the number of questions in each chapter by type.

Chapter / Multiple Choice / True/False / Fill in / Problem / Total
1 / 57 / 40 / 40 / 0 / 137
2 / 52 / 34 / 83 / 18 / 187
3 / 27 / 35 / 34 / 44 / 140
4 / 59 / 15 / 38 / 40 / 152
5 / 26 / 23 / 53 / 74 / 176
6 / 26 / 28 / 43 / 84 / 181
7 / 45 / 65 / 39 / 31 / 180
8 / 29 / 105 / 27 / 26 / 187
9 / 72 / 57 / 28 / 23 / 180
10 / 90 / 25 / 35 / 42 / 192
11 / 55 / 52 / 48 / 26 / 181
12 / 69 / 72 / 37 / 30 / 208
13 / 78 / 33 / 59 / 28 / 198
14 / 110 / 71 / 49 / 28 / 258
15 / 39 / 28 / 11 / 10 / 88
16 / 55 / 29 / 70 / 49 / 203
17 / 78 / 14 / 3 / 32 / 127
18 / 44 / 29 / 35 / 17 / 125
19 / 74 / 8 / 0 / 0 / 82
Total / 1085 / 763 / 732 / 602 / 3182
Keywords Index

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A

a priori classical probability

A2 factor

addition rule

adjusted coefficient of determination

adjusted r-square

aggregate price index

approximate mean

approximate standard deviation

approximate variance

approximation

assumption

autocorrelation

autoregressive model

B

bar chart

base period

Bayes' theorem

beta-risk

binomial distribution

boxplot

C

c chart

capability index

categorical random variable

center line

central limit theorem

Chebyshev rule

chi-square test

Chi-square test for difference in proportions

Chi-square test of independence

choice of analysis

choice of chart

choice of confidence interval estimate

choice of distribution

choice of numerical measures

chunk sample

class boundaries

class interval

class midpoint

cluster sample

coefficient of correlation

coefficient of determination

coefficient of multiple determination

coefficient of partial determination

coefficient of variation

collective exhaustive

collinearity

column percentages

combination

common causes of variation

complement

completely randomized design

component factor

conclusion

conditional probability

confidence coefficient

confidence interval

contingency table

continuity adjustment

continuous random variable

control chart

control limit

convenience sample

counting rule

courses of action

covariance

coverage error

Cp index

C-p statistic

Cpk index

CPL index

CPU index

critical value

cumulative frequency distribution

cumulative percentage distribution

cumulative percentage polygon (ogive)

cumulative relative frequency

D

d2 factor

D3 factor

D4 factor

data

decision

decision making

degrees of freedom

Deming's 14 points

descriptive statistics

deviance statistic

differences among more than two means

difference between two means

difference between two proportions

difference between two variances

discrete random variable

dummy variable

dummy variable

Durbin-Watson statistic

E

empirical classical probability

empirical rule

estimation

estimation of mean values

ethical issues

expected monetary value

expected opportunity loss

expected profit under certainty

expected value

expected value of perfect information

exponential distribution

exponential model

exponential smoothing

F

F distribution

F test

F test for block effects

F test for factor

F test for interaction

F test on slope

F test on the entire regression

finite population correction

fitted value

five-number summary

forecasting

form of hypothesis

frame

frequency distribution

Friedman rank test

G

geometric mean

geometric mean rate of return

H

histogram

Holt-Winters method

homoscedasticity

hypergeometric distribution

inferential statistics

influence analysis

interaction

intercept

interpretation

interquartile range

interval scale

I

Intequartile range

J

joint probability

judgment sample

K

Kruskal-Wallis rank test

L

Laspeyres price index

law of large number

least squares

least squares trend fitting

level of significance

Levene's test

log transformation

logistic regression

M

Marascuilo procedure

marginal probability

maximax

maximin

McNemar test

mean

mean difference

mean of the sum

mean squares

measure of variation

measurement error

measure of central tendency

median

mode

model building

model selection

moving averages

multiplication rule

mutually exclusive

N

nominal scale

nonparametric test

nonprobability sample

nonresponse error

normal distribution

normal probability plot

number of classes

O

objective

odds ratio

one-sided

one-tailed test

one-way analysis of variance

opportunity loss

ordinal scale

outcomes

P

p chart

paired

Paasche price index

parameter

partial F test

payoff

Pareto diagram

percentage distribution

percentage polygon

permutation

pie chart

point estimate

Poisson distribution

polygon

pooled-variance

population

population mean

population variance

population standard deviation

portfolio

power

prediction interval

prediction of individual values

probability

probability distribution

probability sample

process capability

properties

proportion

p-value

Q

quadratic regression

quartile

quota sample

R

R chart

random number

randomized block design

range

rate of return

ratio scale

reasons for learning statistics

reasons for sampling

red bead experiment

rejection region

relative efficiency

relative frequency distribution

residual

residual plot

resistant to outliers

return to risk ratio

risk

robust test

row percentages

S

sample

sample size

sample size determination

sample space

sampling

sampling distribution

sampling error

sampling method

sampling with replacement

sampling without replacement

scatter plot

selection bias

separate-variance

shape

Shewhart-Deming cycle

side-by-side chart

simple price index

simple random sample

six sigma management

slope

sources of data

special causes of variation

standard deviation

standard deviation of sum

standard error

standard error of estimate

standard normal quantile

standardized normal distribution

states of the world

statistic

statistical control

statistical independence

statistical package

statistics

stem-and-leaf display

stepwise regression

stratified sample

subjective probability

sum of squares

survey worthiness

systematic sample

T

t distribution

t test

t test for correlation coefficient

t test on slope

test statistic

testing

time-series plot

total amount

total difference

total percentages

transformation

Tukey procedure

Tukey-Kramer procedure

two-factor analysis of variance

two-factor factorial design

two-tailed test

type I error

type II error

types of data

U

unbiased

uniform distribution

unweighted aggregate price index

utility

V

value

variance

variance inflationary factor

variance of sum

variation

W

Wald statistic

weighted aggregate price index

width

Wilcoxon rank sum test

Wilcoxon signed rank test

X

XBar chart

Z

Z scores

Z test

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