| Description |
1 online resource (xiii, 246 pages) : illustrations |
|
text file |
|
PDF |
| Series |
Expert's voice in data analysis |
|
Expert's voice in data analysis.
|
| Summary |
This book discusses what statistics are really saying or not saying. It shows how to use statistical data to improve small, every-day management judgments as well as major business decisions with potentially serious consequences. This book lays a foundation for understanding the importance and value of big data and shows how mined data can aid business opportunity. Topics covered include: how data is collected, sampled, and best interpreted, to obtain information, with known reliability, for the basis of decision making; the basics of probability, sampling, reliability, regression, distribution and other statistical techniques essential for decision making in all aspects of business; how statistics can help assess the probability of a successful outcome; how to make effective forecasts based on the data at hand; why certainty is illusive and statistical results can be misleading; how to spot the misuse or abuse of statistical evidence in advertisements, reports, and proposals; how to commission a statistical analysis and what it can--and can't--do. This book is a guide for managers and professionals in business and industry; for students of disciplines that require some knowledge of statistics, economics, finance, political science, physics, biology, and more; and for general readers who simply wish to have a more informed view of statistics. |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
Introduction; Part I:Uncertainties; Chapter 1: The Scarcity of Certainty; Chapter 2: Sources of Uncertainty; Statistical Data; Processing the Data; Chapter 3: Probability; Probability Defined; Combining Probabilities; Conditional Probability; Part II:Data; Chapter 4: Sampling; Problems with Sampling; Repeated Measurements; Simple Random Sampling; Systematic Sampling; Stratified Random Sampling; Cluster Sampling; Quota Sampling; Sequential Sampling; Databases; Resampling Methods; Data Sequences; Chapter 5: The Raw Data; Descriptive or Numerical; Format of Numbers; Rounding. |
|
PercentagesSimple Index Numbers; Part III:SamplesThe; Chapter 6: Descriptive Data; Diagrammatic Representation; Proportion; Chapter 7: Numerical Data; Diagrammatic Representation; Normally Distributed Data; Distribution Type; Averages; Spread of Data; Grouped Data; Pooling and Weighting; Estimated Population Properties; Confidence Intervals; Part IV:Comparisons; Chapter 8: Levels of Significance; Chapter 9: General Procedure for Comparisons; Chapter 10: Comparisons with Numerical Data; Single Value; Mean of a Sample; Difference between Variances; Difference between Means; Means of Paired Data. |
|
Multiple SamplesChapter 11: Comparisons with Descriptive Data; Single Proportion; Difference between Proportions; Ranks; Ranks of Paired Data; Duplicate Ranks; Chapter 12: Types of Error; Part V:Relationships; Chapter 13: Cause and Effect; Chapter 14: Relationships with Numerical Data; Linear Relationships; Nonlinear Relationships; Irregular Relationships; Chapter 15: Relationships with Descriptive Data; Nominal Data; Ordinal Data; Chapter 16: Multivariate Data; Multiple Regression; Analysis of Variance; Latin and Graeco-Latin Squares; Multidimensional Contingency Tables. |
|
Multivariate Analysis of VarianceConjoint Analysis; Proximity Maps; Structural Equation Modeling; Association: Some Further Methods; Part VI:Forecasts; Chapter 17: Extrapolation; Chapter 18: Forecasting from Known Distributions; Uniform Distribution; Normal Distribution; Binomial Distribution; Poisson Distribution; Exponential Distribution; Geometric Distribution; Weibull Distribution; Chapter 19: Time Series; Regression; Autocorrelation; Exponential Smoothing; Chapter 20: Control Charts; Sampling by Variable; Sampling by Attribute; Chapter 21: Reliability; Basic Principles; Reliability Data. |
|
DistributionsPractical Complications; Part VII:Big Data; Chapter 22: Data Mining; The Growth of Data; Data Warehouses; Future Developments; Chapter 23: Predictive Analytics; Simple Rules; Decision Trees; Association; Clustering; Neural Networks; Ensembles; Chapter 24: Getting Involved with Big Data; Applications; The Big Players; The Smaller Options; Chapter 25: Concerns with Big Data; Security; Privacy; Skills Shortage; A New Concept; Chapter 26: References and Further Reading; References; Further Reading; Index; Preface; About the Author; Acknowledgments. |
| Language |
English. |
| Subject |
Decision making -- Statistical methods.
|
|
Prise de décision -- Méthodes statistiques. |
|
Decision making -- Statistical methods |
| Other Form: |
Print version: Kenny, Peter, 1935- Better business decisions from data 9781484201848 (OCoLC)883394703 |
| ISBN |
9781484201848 (electronic bk.) |
|
1484201841 (electronic bk.) |
| Standard No. |
10.1007/978-1-4842-0184-8 doi |
|
More Resources