Statistics for Applied Problem Solving and Decision Making

Name: Statistics for Applied Problem Solving and Decision Making
Price: 117.62 USD
Availability: InStock
ISBN: 9780534930844

ISBN-10: 0534930840

ISBN-13: 9780534930844

Edition: 1997

Authors: Richard Larsen, Morris L. Marx, Bruce Cooil

List price: $229.95

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Intended for the applied calculus-based, introductory statistics course for business and economics undergraduates and MBAs, this book presents business statistics as a problem-solving process, rather than as a means to achieve a numerical solution. Applied, data-driven, and copmuter-oriented, it emphasizes the principles of statistics as a foundation for application of statistical methodologies and real-life problems. Curve fitting and regression are introduced early, allowing students to use the computer from the start of the course. Statistical and spreadsheet software help students make the connections between probability models and actual data. The authors include sparing and careful…

Book details

List price: $229.95
Copyright year: 1997
Publisher: Cengage South-Western
Publication date: 3/10/1997
Binding: Hardcover
Pages: 898
Size: 7.75" wide x 9.75" long x 1.25" tall
Weight: 2.794
Language: English



Preface


Introduction


Introduction


The Tools of Statistics


A Brief Course Outline


Statistical Relationships: A First Look


Introduction


Fitting the Model y = b0 + b1x


The Sample Correlation Coefficient


Fitting Curvilinear Relationships


Summary


Samples and Sample Variation


Introduction


Methods of Sampling


Summarizing a Sample


Measuring Location and Dispersion (An Introduction)


Summary


Probability Models: An Introduction


Introduction


Discrete Probability Models


Continuous Probability Models


Summary


The Normal Curve


Introduction


The Standard Normal Curve


The Z Transformation


The Central Limit The orem


Summary


Normal Plots


The Binomial Distribution


Introduction


The Binomial Model


Using Normal Curves to Approximate Binomial Probabilities


Summary


The Hypergeometric, Poisson, and Exponential Distributions


Introduction


The Hypergeometric Distribution


The Poisson and Exponential Distributions


Summary


Proof of The orem 7.3.4


Means and Standard Deviations


Introduction


Expected Value


The Population Standard Deviation


Summary


A Proof of Chebyshev?s Inequality (Theorem 8.3.1)


Estimating Parameters


Introduction


The Method of Maximum Likelihood


Estimators


Margin of Error and Sample Size Determination


Summary


Principles of Inference


Introduction


Testing Hypotheses About u (Normal Data)


Confidence Intervals for u


Drawing Inferences About o2


Binomial Data: Inferences About p


Poisson Data: Inferences About l


Summary


Some Common Types of Data


Introduction


Seven Common Experimental Designs


Summary


Comparing Means


Introduction


The Two-sample t Test


Testing H0: u1 = u2 =


= uk: the One-Way Analysis of Variance


The Paired t Test


Analyzing Randomized Block Data


Summary


Statistical Relationships: A Second Look


Introduction


The Simple Linear Model


Analyzing Categorical Data: the X2 Test for Independence


Summary


Multiple Regression


Introduction


Least Squares Estimation


Hypothesis Testing


Model Building


Prediction Intervals and Influential Observations


Summary


Time Series and Index Numbers


Introduction


Fitting a Time Series Model


Smoothing a Time Series


Simple and Composite Indexes


Weighted Composite Index Numbers


Summary


Quality Control


Introduction


X-charts


R-charts and S-charts


Other Control Charts


Specification Limits Versus Control Limits


Acceptance Sampling


Summary


Appendix A Tables


Bibliography


Answers to Odd-Numbered Exercises


Index