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Data Analysis in Plain English with Microsoft Excel by Harvey J. Brightman (1998, Trade Paperback)

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About this product

Product Identifiers

PublisherBrooks/Cole

ISBN-100534526500

ISBN-139780534526504

eBay Product ID (ePID)850662

Product Key Features

Number of Pages594 Pages

LanguageEnglish

Publication NameData Analysis in Plain English with Microsoft Excel

Publication Year1998

SubjectIndustrial Management, Statistics

TypeTextbook

AuthorHarvey J. Brightman

Subject AreaBusiness & Economics

FormatTrade Paperback

Dimensions

Item Height0.9 in

Item Weight32.1 Oz

Item Length9.1 in

Item Width7.3 in

Additional Product Features

Intended AudienceCollege Audience

LCCN98-028206

Dewey Edition21

ReviewsOutstanding examples and presentation. . . Explains the material without the need for a great understanding of formulas., This is a terrific text! The author has an uncanny knack for explaining concepts and techniques clearly, crisply, and practically, while focusing on the right, important things. I'm impressed! Use of Excel as a supporting tool is right on target. . . The author integrates Excel in a way that is easy to follow and apply, and complements rather than overwhelms the primary focus of the text, which is statistics. He does it as well as (better than) any of the other statistics-with-Excel texts. It should do w|9780534526504|, This is a terrific text! The author has an uncanny knack for explaining concepts and techniques clearly, crisply, and practically, while focusing on the right, important things. I'm impressed! Use of Excel as a supporting tool is right on target. . . The author integrates Excel in a way that is easy to follow and apply, and complements rather than overwhelms the primary focus of the text, which is statistics. He does it as well as (better than) any of the other statistics-with-Excel texts. It should do well in masters and executive programs, as well as in undergraduate programs (at the junior and senior levels).

Dewey Decimal658/.05

Table Of ContentPART I: UNIVARIATE DATA 1. DATA ANALYSIS FOR IMPROVED DECISION MAKING Introduction / Types of Problems / Mental Models and Effective Problem Solving / Types of Variation / Types of Data Business Professionals Use / Data Measurement Scales / Data Sources for Improved Decision Making / Data Collection through Surveys / Summary / Exercises / Appendices 2. DESCRIBING UNIVARIATE DATA Introduction / Management Scenarios and Data Sets / Displaying Cross-Sectional Data for Quantitative Variables / Summarizing Cross-Sectional Data for Quantitative Variables / Assessing Assignable Cause Variation: Cross-Sectional Data for Quantitative Variables / Cross-Sectional Data for Qualitative Variables / Displaying Time-Ordered Data / Summarizing Time-Ordered Data / Assessing Assignable-Cause Variation for Time-Ordered Data / Guide to Data-Analysis Methods / Exercises / Appendices 3. BASIC PROBABILITY CONCEPTS AND PROBLEMS IN ASSESSING PROBABILITIES Introduction / Types of Probability / Computing Conditional Probabilities and Statistical Independence / Using Probability Trees to Minimize Managerial Judgment Errors / Key Ideas / Exercises 4. SAMPLING AND SAMPLING DISTRIBUTIONS The Need for Statistical Inference Methods / Exploring the Distribution of the Sample Mean / The Normal Distribution / Exploring the Distribution of the Sample Proportion / Exploring the Distribution of the Sample Variance / Key Ideas and Overview / Exercises / Appendices 5. STATISTICAL INFERENCE I: CONFIDENCE INTERVALS The Statistical Inference Process / Management Scenarios and Data Sets / General Principles of Confidence Intervals / Confidence Intervals on an Unknown Population Mean / Confidence Interval on an Unknown Population Proportion / Determining the Sample Size / Confidence Interval on an Unknown Population Variance / Key Ideas and Overview / Exercises / Appendices 6. STATISTICAL INFERENCE II: HYPOTHESIS TESTING ON ONE POPULATION PARAMETER Introduction / Management Scenarios and Data Sets / Hypothesis Testing on One Population Mean / Hypothesis Testing on One Population Proportion / Key Ideas and Summary / Exercises / Appendices PART II: MULTIVARIATE DATA 7. DESCRIBING MULTIVARIATE DATA Introduction / Management Scenarios and Data Sets / Analyzing Mixed Cross-Sectional Data / Analyzing Qualitative Cross-Sectional Data / Analyzing Quantitative Cross-Sectional Data / Analyzing Time-Ordered Quantitative Data / Analyzing Time-Ordered Quantitative Data: Autoregressive Equations / Correlation and Cross-Correlation / Guidelines for Using Chapter's Descriptive Methods / Exercises / Appendices 8. HYPOTHESIS TESTING ON TWO POPULATION PARAMETERS Statistical Inference Process / Management Scenarios and Data Sets / Hypothesis Testing on the Difference in the Means of Two Independent Populations Having Equal Variances / Hypothesis Testing on the Difference in the Means of Two Independent Populations Having Unequal Variances / Testing for the Difference between the Means of Two Related Populations: The Paired Sample t-Test for the Matched Pair Design / Testing for the Difference between the Proportions of Two Independent Populations / Testing for the Equality of Variances from Two Independent Populations: The F-test / Roadmap for the Chapter / Exercises / Appendices 9. REGRESSION ANALYSIS AND CHI-SQUARE TEST OF INDEPENDENCE Introduction / Management Scenarios and Data Sets / Introduction to Regression Analysis / Scatter Diagramming and the Analysis of Variance / Evaluating the Regression Model Assumptions: Graphical Analysis of Residuals / Using the Estimated Regression Models for Making Predictions / Multicollinearity / Chi-Square Test of Independence / Chapter Overview / Exercises / Appendices 10. FORECASTING AND TIME SERIES ANALYSIS Data Patterns and Forecasting / Management Scenarios and Data Bases / Forecasting Meandering Patterns / Forecasting Seasonal Patterns / Summary / Exercises / Appendices PART III: QUALITY AREA 11. QUALITY IMPROVEMENT AND STATISTICAL PROCESS CONTRO

SynopsisHarvey Brightman's accessible, easy-to-understand new book focuses on helping readers learn essential statistical concepts and data analysis. In an intuitive and non-mathematical writing style, Brightman uses actual business applications and covers practical insights in business problem solving using Microsoft Excel as the primary computational tool. His clear, to-the-point presentation gives students a 'map' for learning what data analysis techniques to use and when to use them. Brightman presents descriptive and inferential methods in sequential chapters, and introduces probability only as needed and then only on a very limited basis., Harvey Brightman's accessible, easy-to-understand new book focuses on helping readers learn essential statistical concepts and data analysis. In an intuitive and non-mathematical writing style, Brightman uses actual business applications and covers practical insights in business problem solving using Microsoft Excel as the primary computational tool. His clear, to-the-point presentation gives students a 'map' for learning what data analysis techniques to use and when to use them.

LC Classification NumberHA29.B8258 1999