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### Summary

### Summary

Business and marketing professionals have to answer tough questions. How much do 20-to-29-year-olds in New York spend in restaurants? What's the potential market for a $1,200 stereo system? Where can I find customers for a home manicure service? Statistics can be intimidating. How do you use data to determine the direction of your group or product? What are nominal and ordinal variables anyway? In The Complete Idiot's GuideA (R) to Business Statistics, Dr. Sunny Baker gives readers a step-by-step guide to choosing, using, and interpreting statistical analyses for business. The author approaches statistical evaluations as concepts, focusing on the data business people need to interpret and put together, and not on the arithmetic, symbols, and calculations alone. Covering tendency, variables and distributions, this title shows how to use this data for business including sampling, generalizations, analyzing data, and correlation theories. Using real business scenarios as example, The Complete Idiot's GuideA (R) to Business Statistics becomes a handbook for real-life business and marketing professionals.

### Author Notes

Sunny Baker, Ph.D. teaches graduate-level research and statistics courses along with information technology for the University of Redlands. She has also taught at the University of Southern California and San Jose State University. A former general manager at Microsoft and director of marketing at Intel, Sunny has authored or co-authored more than 20 books including the best-selling The Complete Idiot's Guide to Project Management.

### Table of Contents

Part 1 Charting Your Future | p. 1 |

1 Statistics and Business Go Hand in Hand | p. 3 |

The Origin of Statistics | p. 5 |

Some Real-World Business Examples of Statistics | p. 6 |

Introducing the Branches of Statistics | p. 7 |

The Relationship Between Probability and Statistics | p. 9 |

2 Understanding and Organizing Business Data | p. 11 |

Understanding Observations | p. 12 |

Organizing Observations into a Datafile | p. 13 |

Exploring the Four Basic Data Types | p. 14 |

Understanding the Limitations of Your Data Choices | p. 16 |

Start Making Decisions by Creating Datafiles | p. 17 |

3 Visualizing Profit and Performance | p. 21 |

Turning Raw Data into Information | p. 22 |

Examining Relationships with Scatterplots | p. 31 |

Understanding the Types of Variables | p. 34 |

Common Questions About Research Data | p. 36 |

4 Predicting Profits with Measures of Central Tendency | p. 39 |

The Meaning of the Mean | p. 39 |

The Mode--Not an Operation, but a Count | p. 41 |

The Median--In the Middle of Everything | p. 42 |

When to Use a Measure of Central Tendency | p. 44 |

5 Improving Quality with Measures of Dispersion | p. 47 |

Getting Started with Dispersion Measures | p. 48 |

Recognizing the Variance | p. 51 |

Introducing the All-Important Standard Deviation | p. 51 |

6 Solving Problems with Curves and z-Scores | p. 57 |

Introducing the Bell-Shaped Curve | p. 58 |

Measuring the Standard Normal Distribution | p. 59 |

Estimating the Number of Units That Are Substandard | p. 62 |

Predicting Percentages with z-Scores | p. 63 |

Skewed Curves and the Relation to a Standard Distribution | p. 67 |

Part 2 Facing Probability and Forecasting | p. 71 |

7 Playing the Probability Game | p. 73 |

Introducing the Classic Theory of Probability | p. 75 |

Sampling with Replacement | p. 81 |

Dependent Events and Probability | p. 83 |

Exploring Normal Curves and the Binomial Scale | p. 85 |

8 Forecasting Your Business Results | p. 91 |

Introducing the Components of Time Series Data | p. 92 |

Working with Precalculated Business Data | p. 100 |

9 Making Decisions That Count | p. 103 |

Understanding the Key Decisions | p. 104 |

Charting a Decision Tree | p. 105 |

Learning by Example | p. 106 |

Devising Strategies for Decision Making | p. 113 |

Part 3 Using Business Research and Inference | p. 115 |

10 Using Research in Your Business | p. 117 |

Deciding When to Use Research | p. 118 |

Developing a Basic Research Methodology | p. 119 |

Identifying Appropriate Research Projects | p. 120 |

Understanding the Levels of Research | p. 120 |

11 Eliminating the Bias in Your Research | p. 129 |

The Infinite Population in Applied Statistics | p. 130 |

The Importance of Random Sampling | p. 131 |

Choosing the Appropriate Sampling Methods | p. 131 |

How Big Should the Sample Be? | p. 134 |

12 Being Confident About Your Sample | p. 137 |

Conducting Bernoulli Trials | p. 138 |

What About Interval and Ratio Samples? | p. 141 |

Determining a Confidence Interval | p. 143 |

It Won't Work with Small Samples | p. 144 |

13 Testing Your Hypothesis | p. 149 |

Using the Normal Distribution to Answer Questions | p. 149 |

Stating Hypotheses to Test Assumptions | p. 152 |

Using a Five-Step Procedure for Testing a Hypothesis | p. 152 |

Testing a Hypothesis | p. 158 |

14 Learning from Contingency Tables | p. 163 |

How to Create a Contingency Table | p. 164 |

A Real Example of How It Works | p. 169 |

Using Chi Square for Other Expected Frequencies | p. 171 |

Try Using a Contingency Table On Your Own | p. 174 |

Part 4 Seeing the Industry Relationships | p. 175 |

15 Recognizing the Relationships of Business Variables | p. 177 |

Starting with Correlation of Business Variables | p. 178 |

Revealing Hidden Relationships with the Correlation Coefficient | p. 181 |

Going Beyond Correlation to Prediction | p. 184 |

Predicting Business Values | p. 187 |

What Happens When You Have More Variables? | p. 190 |

16 Estimating the Probability of Success with the t-Test | p. 193 |

Understanding the Student's t Distribution | p. 194 |

Using t to Test a Mean | p. 195 |

Comparing Two Population Means Using t | p. 196 |

17 Are These Customers the Same or Different? | p. 205 |

Testing the Mean, Standard Deviation Known | p. 206 |

Working with Proportions and the z Distribution | p. 208 |

Testing Two Population Proportions | p. 211 |

18 Getting Results from ANOVA | p. 215 |

Introducing the F distribution | p. 216 |

Considering Two-Way Analysis of Variance | p. 221 |

Part 5 Going On from Here | p. 225 |

19 Interpreting Business Data Correctly | p. 227 |

Beware of Nonrandom Nonsamples | p. 229 |

Beware the Ploys of Advertisers | p. 229 |

Use the Correct Scale | p. 230 |

Correlation Needs Matched Pairs | p. 231 |

Beware of Significant but Unimportant Findings | p. 232 |

Beware of Data Mining Without Hypotheses | p. 233 |

Avoid Extrapolation That Goes Beyond Observed Ranges | p. 234 |

Avoid Basic Mistakes That Affect Business Results | p. 234 |

From Inferences to Your Future | p. 237 |

20 Using Statistics Programs for Your Company | p. 239 |

Using Software That Simplifies the Details | p. 240 |

What Can Statistics Programs Do? | p. 240 |

The Types of Statistical Programs | p. 242 |

How Do You Choose? | p. 247 |

Things Statistics Software Can't Do | p. 250 |

Go Get Yourself Some! | p. 252 |

21 Advancing Your Business with Statistics | p. 253 |

More Statistical Functions to Learn | p. 254 |

Where Can You Learn More? | p. 256 |

You're Ready to Compute! | p. 258 |

Appendixes | |

A Answer Key | p. 261 |

B Statistics Formulas | p. 267 |

C Sample Statistical Tables | p. 273 |

D A Glossary of Statistical Terms | p. 285 |

Index | p. 303 |