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Introduction to Business Statistics A Microsoft Excel Integrated Approach

by: Kvanli, Alan H.; Pavur, Robert J.; Keeling, Kellie B.

Introduction to Business Statistics A Microsoft Excel Integrated Approach

by: Kvanli, Alan H.; Pavur, Robert J.; Keeling, Kellie B.

ISBN 13:
9780324271560
ISBN 10:
0324271565
Edition: 6th
Format: Hardcover
Copyright: 08/05/2002
Publisher: South-Western College Pub

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Summary

As with earlier editions, this text fully integrates the use of computers with statistics. This edition has retained the non-intimidating approach to describing the concepts and applications of statistics while giving students the opportunity to observe and actually carry out computer-generated solutions using statistics packages like SPSS and MINITAB, or a spreadsheet package like Excel. The text has also been designed so that those requiring a more traditional calculator-based approach will find an abundance of exercises and examples that can be solved in that manner. A CD-ROM presenting data sets and special Excel macros that Robert Pavur (Professor, U of North Texas) and Kellie Keeling (Assistant Professor, Virginia Tech) have created will be bound into the back of the book.

A First Look at Statistics and Data Collection
Statistics in Action: Online Surveys: E-xpress Yourself	p. 1
Using the Computer	p. 3
Uses of Statistics in Business	p. 4
Some Basic Definitions	p. 4
Discrete and Continuous Numerical Data	p. 6
Level of Measurement for Numerical Data	p. 7
Sources of Data	p. 9
Business Research Questions in Practice
Designing and Coding a Questionnaire
Data Presentation Using Descriptive Graphs
Statistics in Action: Lean Philosophy Drives Productivity Growth	p. 25
Frequency Distributions	p. 26
Histograms and Stem-and-Leaf Diagrams	p. 32
Frequency Polygons	p. 40
Cumulative Frequencies (Ogives)	p. 41
Bar Charts	p. 46
Pie Charts	p. 47
Deceptive Graphs	p. 54
Using Computer Graphics	p. 56
Data Summary Using Descriptive Measures
Statistics in Action: Semiconductor Business: When the Chips Are Down	p. 69
Various Types of Descriptive Measures	p. 70
Measures of Central Tendency	p. 71
Measures of Variation	p. 78
Measures of Position	p. 86
Measures of Shape	p. 89
Interpreting X and s	p. 93
Grouped Data	p. 97
Box Plots	p. 101
Probability Concepts
Statistics in Action: Cable and DSL Connections: Wired for Speed	p. 119
Events and Probability	p. 120
Basic Concepts	p. 122
Going Beyond the Contingency Table	p. 129
Applying the Concepts	p. 136
Tree Diagrams	p. 144
Probabilities for More than Two Events	p. 148
Counting Rules	p. 150
Simple Random Samples	p. 155
Discrete Probability Distributions
Statistics in Action: AACSB Accreditation: A Commitment to Excellence in Business Education	p. 167
Random Variables	p. 169
Representing Probability Distributions for Discrete Random Variables	p. 174
Mean and Variance of Discrete Random Variables	p. 177
Binomial Random Variables	p. 183
The Hypergeometric Distribution	p. 194
The Poisson Distribution	p. 198
Continuous Probability Distributions
Statistics in Action: Examining Unethical Behavior: More Fun Than Decent People Think Should Be Legal	p. 215
Continuous Random Variables	p. 216
Normal Random Variables	p. 217
Determining a Probability for a Normal Random Variable	p. 220
Finding Areas Under the Standard Normal Curve	p. 221
Areas Under Any Normal Curve	p. 226
Another Look at the Empirical Rule	p. 233
Using Excel to Determine Areas and Values Having a Specified Area for Normal Populations	p. 233
Normal Approximation to the Binomial	p. 238
Other Continuous Distributions	p. 242
Statistical Inference and Sampling
Statistics in Action: Traffic Congestion Takes Its Toll	p. 259
Random Sampling and the Distribution of the Sample Mean	p. 261
The Central Limit Theorem	p. 267
Confidence Intervals for the Mean of a Normal Population ([sigma] Known)	p. 277
Confidence Intervals for the Mean of a Normal Population ([sigma] Unknown)	p. 286
Selecting the Necessary Sample Size	p. 291
Bootstrap Confidence Intervals
Other Sampling Procedures
Hypothesis Testing for the Mean and Variance of a Population
Statistics in Action: Hillerich & Bradsby Company: Hitting the Quality Mark	p. 303
Hypothesis Testing on the Mean of a Population: Large Sample	p. 305
One-Tailed Test for the Mean of a Population: Large Sample	p. 318
Reporting Testing Results Using a p-Value	p. 325
Hypothesis Testing on the Mean of a Normal Population: Small Sample	p. 332
Inference for the Variance and Standard Deviation of a Normal Population	p. 338
Inference Procedures for Two Populations
Statistics in Action: Rollovers with Sport-Utility Vehicles: Assessing the Impact	p. 355
Independent versus Dependent Samples	p. 356
Comparing Two Means Using Two Large, Independent Samples	p. 358
Comparing Two Normal Population Means Using Two Small, Independent Samples	p. 370
Comparing the Variances of Two Normal Populations Using Independent Samples	p. 382
Comparing the Means of Two Normal Populations Using Paired Samples	p. 391
Estimation and Testing for Population Proportions
Statistics in Action: Streaming Meemies: The Most Valuable Consumer Group on the Internet	p. 411
Estimation and Confidence Intervals for a Population Proportion	p. 413
Hypothesis Testing for a Population Proportion	p. 420
Comparing Two Population Proportions (Large, Independent Samples)	p. 426
Analysis of Variance
Statistics in Action: MBA Programs: Making an Executive Decision to Master Your Career	p. 443
Comparing Two Means: Another Look	p. 445
One-Factor ANOVA Comparing More than Two Means	p. 453
Designing an Experiment	p. 472
Randomized Block Design	p. 475
The Two-Way Factorial Design	p. 490
Quality Improvement
Statistics in Action: Business Excellence: Banking on Six Sigma to Keep Quality Job One	p. 519
Quality Improvement: The Past, Present, and Future	p. 521
The Malcolm Baldrige National Quality Award and ISO 9000 Registration	p. 525
Quality-Improvement Tools	p. 530
Statistical Process Control, Process Variation, and Control Charts	p. 536
Control Charts for Variables Data: The X and R Charts	p. 540
Control Charts for Attribute Data: The p and c Charts	p. 552
Process Capability	p. 560
Applications of the Chi-Square Statistic
Statistics in Action: Data Mining: The Art and Science of Customer Relationship Management	p. 579
Chi-Square Goodness-of-Fit Tests	p. 580
Chi-Square Tests of Independence	p. 597
Correlation and Simple Linear Regression
Statistics in Action: Alpha Beta Soup for the Investor's Soul: Recipe Includes Regression Analysis	p. 621
Bivariate Data and Correlation	p. 622
The Simple Linear Regression Model	p. 634
Inference on the Slope, [beta subscript 1]	p. 640
Measuring the Strength of the Model	p. 649
Estimation and Prediction Using the Simple Linear Model	p. 654
Examining the Residuals	p. 659
Multiple Linear Regression
Statistics in Action: Getting Framed Right Before Your Eyes: Evaluating the Price You Will Pay	p. 687
The Multiple Linear Regression Model	p. 689
Hypothesis Testing and Confidence Intervals for the [beta] Parameters	p. 695
Determining the Predictive Ability of Certain Independent Variables	p. 706
The Problem of Multicollinearity	p. 717
Dummy Variables and Additional Topics in Multiple Linear Regression	p. 724
Model Building	p. 738
Time Series Analysis and Index Numbers
Statistics in Action: Forecasting Underlying Economic Trends: Oh CPI, Why Did You Lie?	p. 759
Components of a Time Series	p. 761
Measuring Trend: No Seasonality	p. 768
Measuring Cyclical Activity: No Seasonality	p. 776
Types of Seasonal Variation	p. 780
Measuring Seasonality	p. 785
A Time Series Containing Seasonality, Trend, and Cycles	p. 793
Index Numbers	p. 804
Quantitative Business Forecasting
Statistics in Action: Going Postal with Forecasting Techniques: Determining Which Methods Receive the Stamp of Approval	p. 819
Methods of Forecasting	p. 821
The Naive Forecast	p. 823
Projecting the Least Squares Trend Equation	p. 826
Simple Exponential Smoothing	p. 830
Exponential Smoothing for a Time Series Containing Trend	p. 836
Exponential Smoothing Method for Trend and Seasonality	p. 840
Choosing the Appropriate Forecasting Procedure	p. 847
Autoregressive Forecasting Techniques
The Other Side of Forecasting: Linear Regression Using Time Series Data
The Problem of Autocorrelation: The Durbin-Watson Statistic
Nonparametric Statistics
Statistics in Action: Putting Service Back into Customer Service: Assessing Survey Data to Get Blue Oval Certified	p. 869
A Test for Randomness: The Runs Test	p. 871
Nonparametric Tests of Central Tendency: Two Populations	p. 880
Comparing More than Two Populations: The Kruskal-Wallis Test and the Friedman Test	p. 897
A Measure of Association: Spearman Rank Correlation
An Alternative to the Least Squares Regression Line: A Nonparametric Approach
Decision Making Under Uncertainty (on CD)
Statistics in Action: Stealth Manufacturers: Using Decision Strategies to Make Products That Tech Giants Put Their Names On
Defining the Decision Problem
Decision Strategies
The Concept of Utility
Decision Trees and Bayes' Rule
Appendixes
Tables	p. 1
Answers to Odd-Numbered Exercises	p. 40
Introduction to Excel
Introduction to SPSS
Introduction to MINITAB
Database Using Household Financial Variables
Database Using Financial Variables of Companies
Derivation of Minimal Total Sample Size
Index	p. 1
Table of Contents provided by Syndetics. All Rights Reserved.

Amazon no longer offers textbook rentals. We do!

Introduction to Business Statistics A Microsoft Excel Integrated Approach

Introduction to Business Statistics A Microsoft Excel Integrated Approach

9780324271560

0324271565

Summary

Table of Contents

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