Beschreibung
Everyone encounters statistics on a daily basis. They are used in proposals, reports, requests, and advertisements, among others, to support assertions, opinions, and theories. Unless you’re a trained statistician, it can be bewildering. What are the numbers really saying or not saying? Better Business Decisions from Data: Statistical Analysis for Professional Success provides the answers to these questions and more. It will show you how to use statistical data to improve small, every-day management judgments as well as major business decisions with potentially serious consequences.Author Peter Kenny—with deep experience in industry—believes that "while the methods of statistics can be complicated, the meaning of statistics is not." He first outlines the ways in which we are frequently misled by statistical results, either because of our lack of understanding or because we are being misled intentionally. Then he offers sound approaches for understanding and assessing statistical data to make excellent decisions. Kenny assumes no prior knowledge of statistical techniques; he explains concepts simply and shows how the tools are used in various business situations.With the arrival of Big Data, statistical processing has taken on a new level of importance. Kenny lays a foundation for understanding the importance and value of Big Data, and then he shows how mined data can help you see your business in a new light and uncover opportunity.Among other things, this book covers: - How statistics can help you assess the probability of a successful outcome How data is collected, sampled, and best interpreted How to make effective forecasts based on the data at hand How to spot the misuse or abuse of statistical evidence in advertisements, reports, and proposals How to commission a statistical analysis Arranged in seven parts—Uncertainties, Data, Samples, Comparisons, Relationships, Forecasts, and Big Data—Better Business Decisions from Data is a guide for busy people in general management, finance, marketing, operations, and other business disciplines who run across statistics on a daily or weekly basis. You’ll return to it again and again as new challenges emerge, making better decisions each time that boost your organization’s fortunes—as well as your own.
Autorenporträt
InhaltsangabePart I. UncertaintiesChapter 1. The Scarcity of Certainty: What Time Will the Next Earthquake Be?Chapter 2. Sources of Uncertainty: Why "Sure Thing!" Rarely IsChapter 3. Probability: How Bad Statistics Can Put You in Jail Part II. DataChapter 4. Sampling: Did Nine out of Ten Really Say That? Chapter 5. The Raw Data: Hard to Digest Until Processed Part III. SamplesChapter 6. Descriptive Data: Not Every Picture Is Worth a Thousand WordsChapter 7. Numerical Data: Are Your Statistics Normal? Part IV. ComparisonsChapter 8. Levels of Significance: What Odds Are You Giving?Chapter 9. General Procedure for Comparisons: Eight Easy Steps--As Always Chapter 10. Comparisons with Numerical Data: Are Today's Chocolate Bars Smaller Than Yesterday's?Chapter 11. Comparisons with Descriptive Data: Is Your Staff Female/Male Ratio OK?Chapter 12. Types of Error: How Wrong Can You Be? Part V. RelationshipsChapter 13. Cause and Effect: Gooseberry Bushes and Birth RatesChapter 14. Relationships with Numerical Data: Straight Lines, Curved Lines, and Wiggly LinesChapter 15. Relationships with Descriptive Data: Any Color As Long As It's BlackChapter 16. Multivariate Data: Variety Is the Spice of Life Part VI. ForecastsChapter 17. Extrapolation: Malthus Got It WrongChapter 18. Forecasting from Known Distributions: Why Does The Phone Never Stop Ringing?Chapter 19. Time Series: Yesterday Rain, Today Rain, Tomorrow.?Chapter 20. Control ChartsChapter 21. Reliability: Would You Trust That Bungee Rope? Part VII. Big DataChapter 22. Data Mining: Twenty-First-Century Gold RushChapter 23. Predictive Analytics: It's Only Arithmetic!Chapter 24. Getting Involved with Big DataChapter 25. Concerns with Big Data: The Small Print
