Schaum's Easy Outline of Business Statistics

Download Schaum's Easy Outline of Business Statistics

Post on 21-Dec-2016

216 views

Category:

Documents

1 download

TRANSCRIPT

  • SCHAUMS Easy OUTLINES

    BUSINESSSTATISTICS

    LD7479.i-viii 12/24/02 11:46 AM Page i

  • Other Books in SchaumsEasy Outlines Series Include:

    Schaums Easy Outline: CalculusSchaums Easy Outline: College AlgebraSchaums Easy Outline: College MathematicsSchaums Easy Outline: Differential EquationsSchaums Easy Outline: Discrete MathematicsSchaums Easy Outline: Elementary AlgebraSchaums Easy Outline: GeometrySchaums Easy Outline: Linear AlgebraSchaums Easy Outline: Mathematical Handbook

    of Formulas and TablesSchaums Easy Outline: PrecalculusSchaums Easy Outline: Probability and StatisticsSchaums Easy Outline: StatisticsSchaums Easy Outline: TrigonometrySchaums Easy Outline: Principles of AccountingSchaums Easy Outline: Principles of EconomicsSchaums Easy Outline: BiologySchaums Easy Outline: BiochemistrySchaums Easy Outline: Molecular and Cell BiologySchaums Easy Outline: College ChemistrySchaums Easy Outline: GeneticsSchaums Easy Outline: Human Anatomy

    and PhysiologySchaums Easy Outline: Organic ChemistrySchaums Easy Outline: Applied PhysicsSchaums Easy Outline: PhysicsSchaums Easy Outline: Programming with C++Schaums Easy Outline: Programming with JavaSchaums Easy Outline: Basic ElectricitySchaums Easy Outline: ElectromagneticsSchaums Easy Outline: Introduction to PsychologySchaums Easy Outline: FrenchSchaums Easy Outline: German Schaums Easy Outline: SpanishSchaums Easy Outline: Writing and Grammar

    LD7479.i-viii 12/24/02 11:46 AM Page ii

  • SCHAUMS Easy OUTLINES

    BUSINESS STATISTICS

    B a s e d o n S c h a u m s

    Out l ine o f Theory and Problems o f

    Bus iness S ta t i s t ics , Third Edi t ion

    b y L e o n a r d J . K a z m i e r , Ph.D.

    A b r i d g e m e n t E d i t o r s

    D a n i e l L . F u l k s , Ph.D.and

    Michael K. Staton

    S C H A U M S O U T L I N E S E R I E SM c G R AW - H I L L

    New York Chicago San Francisco Lisbon London Madrid

    Mexico City Milan New Delhi San Juan

    Seoul Singapore Sydney Toronto

    LD7479.i-viii 12/24/02 11:46 AM Page iii

  • Copyright 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Manufactured in theUnited States of America. Except as permitted under the United States Copyright Act of 1976, no partof this publication may be reproduced or distributed in any form or by any means, or stored in a data-base or retrieval system, without the prior written permission of the publisher.

    0-07-142584-5

    The material in this eBook also appears in the print version of this title: 0-07-139876-7

    All trademarks are trademarks of their respective owners. Rather than put a trademark symbol afterevery occurrence of a trademarked name, we use names in an editorial fashion only, and to the benefitof the trademark owner, with no intention of infringement of the trademark. Where such designationsappear in this book, they have been printed with initial caps.

    McGraw-Hill eBooks are available at special quantity discounts to use as premiums and sales pro-motions, or for use in corporate training programs. For more information, please contact GeorgeHoare, Special Sales, at george_hoare@mcgraw-hill.com or (212) 904-4069.

    TERMS OF USEThis is a copyrighted work and The McGraw-Hill Companies, Inc. (McGraw-Hill) and its licensorsreserve all rights in and to the work. Use of this work is subject to these terms. Except as permittedunder the Copyright Act of 1976 and the right to store and retrieve one copy of the work, you may notdecompile, disassemble, reverse engineer, reproduce, modify, create derivative works based upon,transmit, distribute, disseminate, sell, publish or sublicense the work or any part of it withoutMcGraw-Hills prior consent. You may use the work for your own noncommercial and personal use;any other use of the work is strictly prohibited. Your right to use the work may be terminated if youfail to comply with these terms.

    THE WORK IS PROVIDED AS IS. McGRAW-HILL AND ITS LICENSORS MAKE NO GUAR-ANTEES OR WARRANTIES AS TO THE ACCURACY, ADEQUACY OR COMPLETENESS OFOR RESULTS TO BE OBTAINED FROM USING THE WORK, INCLUDING ANY INFORMA-TION THAT CAN BE ACCESSED THROUGH THE WORK VIA HYPERLINK OR OTHERWISE,AND EXPRESSLY DISCLAIM ANY WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUTNOT LIMITED TO IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR APARTICULAR PURPOSE. McGraw-Hill and its licensors do not warrant or guarantee that the func-tions contained in the work will meet your requirements or that its operation will be uninterrupted orerror free. Neither McGraw-Hill nor its licensors shall be liable to you or anyone else for any inac-curacy, error or omission, regardless of cause, in the work or for any damages resulting therefrom.McGraw-Hill has no responsibility for the content of any information accessed through the work.Under no circumstances shall McGraw-Hill and/or its licensors be liable for any indirect, incidental,special, punitive, consequential or similar damages that result from the use of or inability to use thework, even if any of them has been advised of the possibility of such damages. This limitation of lia-bility shall apply to any claim or cause whatsoever whether such claim or cause arises in contract, tortor otherwise.

    DOI: 10.1036/0071425845

    ebook_copyright 8 x 10.qxd 7/7/03 5:09 PM Page 1

  • Want to learn more?

    We hope you enjoy this McGraw-Hill eBook! If you d likemore information about this book, its author, or related booksand websites, please click here.

    DOI Page 6x9 10/2/02 1:33 PM Page 1

    ,

  • Contents

    v

    Chapter 1 Analyzing Business Data 1Chapter 2 Statistical Presentations

    and Graphical Displays 7Chapter 3 Describing Business Data:

    Measures of Location 18Chapter 4 Describing Business Data:

    Measures of Dispersion 26Chapter 5 Probability 37Chapter 6 Probability Distributions

    for Discrete Random Variables:Binomial, Hypergeometric, and Poisson 46

    Chapter 7 Probability Distributions for Continuous Random Variables:Normal and Exponential 54

    Chapter 8 Sampling Distributions and Confidence Intervals for the Mean 60

    Chapter 9 Other Confidence Intervals 72Chapter 10 Testing Hypotheses Concerning

    the Value of the Population Mean 80Chapter 11 Testing Other Hypotheses 94Chapter 12 The Chi-Square Test for the

    Analysis of Qualitative Data 106Chapter 13 Analysis of Variance 113

    LD7479.i-viii 12/24/02 11:46 AM Page v

    For more information about this title, click here.

    Copyright 2003 by The McGraw-Hill Companies, Inc. Click here for Terms of Use.

  • Chapter 14 Linear Regression and CorrelationAnalysis 124

    Chapter 15 Multiple Regression and Correlation 135Chapter 16 Time Series Analysis and Business

    Forecasting 143Chapter 17 Decision Analysis: Payoff Tables

    and Decision Trees 155Chapter 18 Statistical Process Control 162Appendices 168Index 173

    vi BUSINESS STATISTICS

    LD7479.i-viii 12/24/02 11:46 AM Page vi

  • SCHAUMS Easy OUTLINES

    BUSINESSSTATISTICS

    LD7479.i-viii 12/24/02 11:46 AM Page vii

  • This page intentionally left blank.

  • Chapter 1

    AnalyzingBusiness Data

    In This Chapter:

    Definition of Business Statistics Descriptive and Inferential Statistics Types of Applications in Business Discrete and Continuous Variables Obtaining Data through Direct

    Observation vs. Surveys Methods of Random Sampling Other Sampling Methods Solved Problems

    Definition of Business Statistics

    Statistics refers to the body of techniques used for collecting, organizing,analyzing, and interpreting data. The data may be quantitative, with val-ues expressed numerically, or they may be qualitative, with characteris-tics such as consumer preferences being tabulated. Statistics are used inbusiness to help make better decisions by understanding the sources ofvariation and by uncovering patterns and relationships in business data.

    1

    LD7479.001-006 12/24/02 11:48 AM Page 1

    Copyright 2003 by The McGraw-Hill Companies, Inc. Click here for Terms of Use.

  • Descriptive and Inferential Statistics

    Descriptive statistics include the techniques that are used to summarizeand describe numerical data for the purpose of easier interpretation.These methods can either be graphical or involve computational analy-sis.

    Inferential statistics include those tech-niques by which decisions about a statisticalpopulation or process are made based onlyon a sample having been observed. Becausesuch decisions are made under conditions ofuncertainty, the use of probability conceptsis required. Whereas the measured charac-teristics of a sample are called sample sta-tistics, the measured characteristics of a sta-tistical population are called populationparameters. The procedure by which the characteristics of all the mem-bers of a defined population are measured is called a census. When sta-tistical inference is used in process control, the sampling is concernedparticularly with uncovering and controlling the sources of variation inthe quality of the output.

    Types of Applications in Business

    The methods of classical statistics were developed for the analysis ofsample data, and for the purpose of inference about the population fromwhich the sample was selected. There is explicit exclusion of personaljudgments about the data, and there is an implicit assumption that sam-pling is done from a static population. The methods of decision analysisfocus on incorporating managerial judgments into statistical analysis.The methods of statistical process control are used with the premise thatthe output of a process may not be stable. Rather, the process may be dy-namic, with assignable causes associated with variation in the quality ofthe output over time.

    Discrete and Continuous Variables

    Adiscrete variable can have observed values only at isolated points alonga scale of values. In business statistics, such data typically occur through

    2 BUSINESS STATISTICS

    LD7479.001-006 12/24/02 11:48 AM Page 2

  • the process of counting; hence, the values generally are expressed as in-tegers. A continuous variable can assume a value at any fractional pointalong a specified interval of values.

    You Need to Know

    Continuous data are generated by the process ofmeasuring.

    Obtaining Data through Direct Observation vs. Surveys

    One way data can be obtained is by direct observation. This is the basisfor the actions that are taken in statistical process control, in which sam-ples of output are systemically assessed. Another form of direct observa-tion is a statistical experiment, in which there is overt control over someor all of the factors that may influence the variable being studied, so thatpossible causes can be identified.

    In some situations it is not possible to collect data directly but, rather,the information has to be obtained from individual respondents. A statis-tical survey is the process of collecting data by asking individuals to pro-vide the data. The data may be obtained through such methods as per-sonal interviews, telephone interviews, or written questionnaires.

    Methods of Random Sampling

    Random sampling is a type of sampling in which every item in a popula-tion of interest, or target population, has a known, and usually equal,chance of being chosen for inclusion in the sample. Having such a sam-ple ensures that the sample items are chosen without bias and providesthe statistical basis for determining the confidence that can be associatedwith the inferences. A random sample is also called a probability sample,or scientific sample. The four principal methods of random sampling arethe simple, systematic, stratified, and cluster sampling methods.

    A simple random sample is one in which items are chosen individu-

    CHAPTER 1: Analyzing Business Data 3

    LD7479.001-006 12/24/02 11:48 AM Page 3

  • ally from the target population on the basis of chance.Such chance selection is similar to the random draw-ing of numbers in a lottery. However, in statisticalsampling a table of random numbers or a randomnumber generator computer program generally isused to identify the numbered items in the populationthat are to be selected for the sample.

    A systematic sample is a random sample in which the items are se-lected from the population at a uniform interval of a listed order, such aschoosing every tenth account receivable for the sample. The first accountof the ten accounts to be included in the sample would be chosen ran-domly (perhaps by reference to a table of random numbers). A particularconcern with systematic sampling is the existence of any periodic, orcyclical, factor in the population listing that could lead to a systematic er-ror in the sample results.

    In stratified sampling the items in the population are first classifiedinto separate subgroups, or strata, by the researcher on the basis of one ormore important characteristics. Then a simple random or systematic sam-ple is taken separately from each stratum. Such a sampling plan can beused to ensure proportionate representation of various population sub-groups in the sample. Further, the required sample size to achieve a giv-en level of precision typically is smaller than it is with random sampling,thereby reducing sampling cost.

    Cluster sampling is a type of random sampling in which the popula-tion items occur naturally in subgroups. Entire subgroups, or clusters, arethen randomly sampled.

    Other Sampling Methods

    Although a nonrandom sample can turn out to be representative of thepopulation, there is difficulty in assuming beforehand that it will be un-biased, or in expressing statistically the confidence that can be associat-ed with inferences from such a sample.

    A judgment sample is one in which an individual selects the items tobe included in the sample. The extent to which such a sample is repre-sentative of the population then depends on the judgment of that individ-ual and cannot be statistically assessed.

    A convenience sample includes the most easily accessible measure-ments, or observations, as is implied by the word convenience.

    4 BUSINESS STATISTICS

    LD7479.001-006 12/24/02 11:48 AM Page 4

  • A strict random sample is not usually feasible in statistical processcontrol, since only readily available items or transactions can easily beinspected. In order to capture changes that are taking place in the qualityof process output, small samples are taken at regular intervals of time.Such a sampling scheme is called the method of rational subgroups. Suchsample data are treated as if random samples were taken at each point intime, with the understanding that one should be alert to any known rea-sons why such a sampling scheme could lead to biased results.

    Remember

    The four principal methods of ran-dom sampling are the simple, sys-tematic, stratified, and cluster sam-pling methods.

    Solved Problems

    Solved Problem 1.1 Indicate which of the following terms or operationsare concerned with a sample or sampling (S), and which are concernedwith a population (P): (a) group measures called parameters, (b) use ofinferential statistics, (c) taking a census, (d) judging the quality of an in-coming shipment of fruit by inspecting several crates of the large num-ber included in the shipment.

    Solution: (a) P, (b) S, (c) P, (d) S...

Recommended

View more >