TATISTICS FOR BUSINESS

S

OLUTIONS MANUAL

NANCY BOUDREAU

S

TATISTICS FOR BUSINESS

AND ECONOMICS

T

HIRTEENTH EDITION

By James T. McClave

• George Benson

Terry Sincich 1 / 4

Contents

• Statistics, Data, and Statistical Thinking 1
• Methods for Describing Sets of Data 10
• Probability 94
• Random Variables and Probability Distributions 142
• Sampling Distributions 247
• Inferences Based on a Single Sample: Estimation with Confidence Intervals 282

7. Inferences Based on a Single Sample: Tests of Hypotheses 332

• Inferences Based on Two Samples: Confidence Intervals and Tests of Hypotheses 398
• Design of Experiments and Analysis of Variance 484
• Categorical Data Analysis 546
• Simple Linear Regression 591
• Multiple Regression and Model Building 672

13. Methods for Quality Improvement: Statistical Process Control 799

14. Time Series: Descriptive Analyses, Models, and Forecasting 863

• Nonparametric Statistics 943 2 / 4

1 Chapter 1 Statistics, Data, and Statistical Thinking 1.1 Statistics is a science that deals with the collection, classification, analysis, and interpretation of information or data. It is a meaningful, useful science with a broad, almost limitless scope of applications to business, government, and the physical and social sciences.

1.2 Descriptive statistics utilizes numerical and graphical methods to look for patterns, to summarize, and to present the information in a set of data. Inferential statistics utilizes sample data to make estimates, decisions, predictions, or other generalizations about a larger set of data.

1.3 The four elements of a descriptive statistics problem are:

• The population or sample of interest. This is the collection of all the units upon which the variable is

measured.

• One or more variables that are to be investigated. These are the types of data that are to be collected.
• Tables, graphs, or numerical summary tools. These are tools used to display the characteristic of the

sample or population.

• Identification of patterns in the data. These are conclusions drawn from what the summary tools

revealed about the population or sample.

1.4 The five elements of an inferential statistical analysis are:

• The population of interest. The population is a set of existing units.
• One or more variables that are to be investigated. A variable is a characteristic or property of an

individual population unit.

• The sample of population units. A sample is a subset of the units of a population.
• The inference about the population based on information contained in the sample. A statistical

inference is an estimate, prediction, or generalization about a population based on information contained in a sample.

• A measure of reliability for the inference. The reliability of an inference is how confident one is that

the inference is correct.

1.5 The first major method of collecting data is from a published source. These data have already been collected by someone else and are available in a published source. The second method of collecting data is from a designed experiment. These data are collected by a researcher who exerts strict control over the experimental units in a study. These data are measured directly from the experimental units. The final method of collecting data is observational. These data are collected directly from experimental units by simply observing the experimental units in their natural environment and recording the values of the desired characteristics. The most common type of observational study is a survey.

1.6 Quantitative data are measurements that are recorded on a meaningful numerical scale. Qualitative data are measurements that are not numerical in nature; they can only be classified into one of a group of categories.

1.7 A population is a set of existing units such as people, objects, transactions, or events. A variable is a characteristic or property of an individual population unit such as height of a person, time of a reflex, amount of a transaction, etc. 3 / 4

Chapter 1 Copyright © 2018 Pearson Education, Inc.2 1.8 A population is a set of existing units such as people, objects, transactions, or events. A sample is a subset of the units of a population.

1.9 A representative sample is a sample that exhibits characteristics similar to those possessed by the target population. A representative sample is essential if inferential statistics is to be applied. If a sample does not possess the same characteristics as the target population, then any inferences made using the sample will be unreliable.

1.10 An inference without a measure of reliability is nothing more than a guess. A measure of reliability separates statistical inference from fortune telling or guessing. Reliability gives a measure of how confident one is that the inference is correct.

1.11 A population is a set of existing units such as people, objects, transactions, or events. A process is a series of actions or operations that transform inputs to outputs. A process produces or generates output over time.Examples of processes are assembly lines, oil refineries, and stock prices.

1.12 Statistical thinking involves applying rational thought processes to critically assess data and inferences made from the data. It involves not taking all data and inferences presented at face value, but rather making sure the inferences and data are valid.

1.13 The data consisting of the classifications A, B, C, and D are qualitative. These data are nominal and thus are qualitative. After the data are input as 1, 2, 3, and 4, they are still nominal and thus qualitative. The only differences between the two data sets are the names of the categories. The numbers associated with the four groups are meaningless.

1.14 Answers will vary. First, number the elements of the population from 1 to 200,000. Using MINITAB, generate 10 numbers on the interval from 1 to 200,000, eliminating any duplicates.

The 10 numbers selected for the random sample are:

135075

89127

189226

83899

112367

191496

110021

44853 42091

198461

Elements with the above numbers are selected for the sample.

1.15 Both the variables current position and type of organization are qualitative. The variable years of experience is quantitative.

1.16 a.The data would represent the population. These data are all of the data that are of interest to th e research ers.

• If the 80 jamming attacks are actually a sample, then the population would be all jamming attacks by

the U.S. military over the past seve ral years.c.The variable “network type” is qualitativ

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