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内容简介:
You too can understand the statistics of life, even if you're
math-challenged What do you need to calculate? Manufacturing
output? A curve for test scores? Sports stats? You and Excel can do
it, and this non-intimidating guide shows you how. It demystifies
the different types of statistics, how Excel functions and formulas
work, the meaning of means and medians, how to interpret your
figures, and more -- in plain English. Getting there -- learn how
variables, samples, and probability are used to get the information
you want Excel tricks -- find out what's built into the program to
help you work with Excel formulas Playing with worksheets -- get
acquainted with the worksheet functions for each step Graphic
displays -- present your data as pie graphs, bar graphs, line
graphs, or scatter plots What's normal? -- understand normal
distribution and probability Hyping hypotheses -- learn to use
hypothesis testing with means and variables When regression is
progress -- discover when and how to use regression for forecasting
What are the odds -- work with probability, random variables, and
binomial distribution Open the book and find: Ten statistical and
graphical tips and traps The difference between de*ive and
inferential statistics Why graphs are good How to measure
variations What standard scores are and why they're used When to
use two-sample hypothesis testing How to use correlations Different
ways of working with probability
书籍目录:
Introduction
Part I: Statistics and Excel: A Marriage Made in Heaven
Chapter 1: Evaluating Data in the Real World
Chapter 2: Understanding Excel's Statistical Capabilities
Part II: Describing Data
Chapter 3: Show and Tell: Graphing Data
Chapter 4: Finding Your Center
Chapter 5: Deviating from the Average
Chapter 6: Meeting Standards and Standings
Chapter 7: Summarizing It All
Chapter 8: What's Normal? Part III: Drawing Conclusions from
Data
Chapter 9: The Confi dence Game: Estimation
Chapter 10: One-Sample Hypothesis Testing
Chapter 11: Two-Sample Hypothesis Testing
Chapter 12: Testing More Than Two Samples
Chapter 13: Slightly More Complicated Testing
Chapter 14: Regression: Linear and Multiple
Chapter 15: Correlation: The Rise and Fall of Relationships
Part IV: Working with Probability
Chapter 16: Introducing Probability
Chapter 17: More on Probability
Chapter 18: A Career in Modeling
Part V: The Part of Tens
Chapter 19: Ten Statistical and Graphical Tips and Traps
Chapter 20: Ten Things (Twelve, Actually) That Didn't Fit in Any
Other Chapter
Appendix A: When Your Worksheet Is a Database
Appendix B: The Analysis of Covariance
Appendix C: Of Stems, Leaves, Boxes, Whiskers, and Smoothies
Index.
作者介绍:
Joseph Schmuller, PhD, is a technical architect at Blue
Cross-Blue Shield of Florida. A former member of the American
Statistical Association, he has taught statistics at the
undergraduate, honors undergraduate, and graduate levels, and has
been honored with an award for excellence in teaching.
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书籍介绍
You too can understand the statistics of life, even if you're math-challenged What do you need to calculate? Manufacturing output? A curve for test scores? Sports stats? You and Excel can do it, and this non-intimidating guide shows you how. It demystifies the different types of statistics, how Excel functions and formulas work, the meaning of means and medians, how to interpret your figures, and more -- in plain English. Getting there -- learn how variables, samples, and probability are used to get the information you want Excel tricks -- find out what's built into the program to help you work with Excel formulas Playing with worksheets -- get acquainted with the worksheet functions for each step Graphic displays -- present your data as pie graphs, bar graphs, line graphs, or scatter plots What's normal? -- understand normal distribution and probability Hyping hypotheses -- learn to use hypothesis testing with means and variables When regression is progress -- discover when and how to use regression for forecasting What are the odds -- work with probability, random variables, and binomial distribution Open the book and find: Ten statistical and graphical tips and traps The difference between descriptive and inferential statistics Why graphs are good How to measure variations What standard scores are and why they're used When to use two-sample hypothesis testing How to use correlations Different ways of working with probability
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