Minitab Table of Contents

Detailed Table of Contents

Preface

Part I INTRODUCTION

1. The Nature of Statistics

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1.1 INTRODUCTION

1.2 COLLECTING DATA

Finding Existing Data
Generating New Data

1.3 DESCRIBING DATA

1.4 ANALYZING DATA

Drawing Inferences by Inductive Reasoning
Drawing Inferences by Deductive Reasoning
Looking Ahead

1.5 STATISTICS—A UNIVERSAL GUIDE TO THE UNKNOWN

1.6 BASIC STATISTICAL CONCEPTS

Elementary Units and the Frame
Variables and Data
Qualitative and Quantitative Variables
Population Versus Sample

1.7 MAJOR TYPES OF DATA

Nominal Data
Ordinal Data
Interval Data

APPLICATION 1.1 Time in Cyberspace

Ratio Data

2. Learning About MINITAB

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2.1 INTRODUCTION

2.2 THE MINITAB ENVIRONMENT

MINITAB Windows
Menus and Tools
Session Commands

2.3 THE STAGES OF A TYPICAL PROJECT

Starting a New Project
Entering Data
Manipulating Data
Producing Descriptive Statistics
Drawing Inferences
Saving Your Work
Concluding Your Work

2.4 ENTERING DATA

Three Data Types
Three Data Forms
Typing Data Into the Data Window
Copying and Pasting Data
Generating Data Within MINITAB
Opening a MINITAB Data File

2.5 MANIPULATING DATA

Manipulating Cells, Rows, and Columns
Subsetting and Splitting Data
Stacking Columns
Coding Data
Sorting Data
Using the Calculator

2.6 PRODUCING DESCRIPTIVE STATISTICS

Arithmetic Summary Measures
Graphs

2.7 DRAWING INFERENCES

2.8 SESSION COMMANDS AND MACROS

Using the Session Window
Examples of Session Commands
Basic Rules for Typing Session Commands
Using the Command Line Editor
Using Macros

2.9 GETTING HELP

MINITAB's Built-In Help Feature
MINITAB on the Internet

Part II COLLECTING DATA

3. Finding Existing Data: From Print to the Internet

PREVIEW

3.1 INTRODUCTION

3.2 FINDING DATA IN PRINT

3.3 BASIC INTERNET CONCEPTS

Internet Versus World Wide Web
Conventions Governing the Web
Searching the Web
Boolean Logic and Such

3.4 FINDING DATA ON THE WORLD WIDE WEB

U.S. Government Sources
Foreign Government Sources
Fortune 500
Company Sources
Other Interesting Data Sources

3.5 HOW TO GRAB DATA OFF THE WEB

Copy and Paste
Possible Complications
Special Procedures

4. Generating New Data: Census Taking and Sampling

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4.1 CENSUS TAKING VERSUS SAMPLING

APPLICATION 4.1 Great Censuses of the 1990s

APPLICATION 4.2 Sampling as Legal Evidence

4.2 THE REASONS FOR SAMPLING

Prohibitive Cost of a Census
Physical Impossibility of a Census
Destructive Nature of a Census
Lack of Time for a Census
More Information Per Dollar With Sampling
More Accurate Information With Sampling

4.3 TWO BASIC TYPES OF SAMPLES

Nonprobability Samples
Probability Samples

4.4 THE SIMPLE RANDOM SAMPLE

Exploring the Definition
Selecting the Sample
Using the Random-Numbers Table
Using a Computer's Random-Numbers Generator
Drawbacks

APPLICATION 4.3 The 1970 Draft Lottery Fiasco

4.5 OTHER TYPES OF RANDOM SAMPLES

The Systematic Random Sample
The Stratified Random Sample

APPLICATION 4.4 How Accountants Save Money By Sampling

The Clustered Random Sample

4.6 MULTISTAGE SAMPLES

4.7 ERRORS IN SURVEY DATA

Random Error
Systematic Error or Bias

4.8 HOW BIAS CREEPS INTO SURVEYS

Selection Bias
Nonresponse Bias

APPLICATION 4.5 The Politics of Census 2000

Response Bias

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5. Generating New Data: Controlled Experiments

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5.1 ASSOCIATION VERSUS CAUSATION

Association Revealed By Surveys
Causation Established By Experiments
The Limits of Experimentation

APPLICATION 5.1 The Negative Income Tax Experiments

5.2 THE DESIGN OF EXPERIMENTS

Basic Concepts
Steps in Valid Experiments
The Confounding Problem

APPLICATION 5.2 On Curing the Common Cold and Other Diseases

Randomization and Blocking

5.3 THE RANDOMIZED GROUP DESIGN

5.4 THE RANDOMIZED BLOCK DESIGN

APPLICATION 5.3 Confounding and Blocking: The Fluorescein Experiment

5.5 COMPLEX DESIGNS

The Crossover Design
The Latin Square Design
The Youden Square Design

5.6 ERRORS IN EXPERIMENTAL DATA

Random Error or Experimental Error
Systematic Error or Bias

APPLICATION 5.4 Selection Bias in the Salk Polio Vaccine Trial

APPLICATION 5.5 New Profits From Old Compounds

Part III Descriptive Statistics

6. Presenting Data: Tables and Graphs

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6.1 AN INTRODUCTION TO TABLE MAKING

Confusing Tables
Ordered Arrays

6.2 THE ABSOLUTE FREQUENCY DISTRIBUTION

The Nature of Data Classes
Collectively Exhaustive Classes
Mutually Exclusive Classes
The Desirable Number of Classes
The Desirable Width of Classes
The Final Product Derived
The Final Product Assessed

6.3 THE RELATIVE FREQUENCY DISTRIBUTION

APPLICATION 6.1 Deciphering Secret Codes

6.4 CUMULATIVE FREQUENCY DISTRIBUTIONS

6.5 CROSS-TABULATIONS

6.6 AN INTRODUCTION TO DRAWING GRAPHS

6.7 FREQUENCY HISTOGRAMS

Depicting an Absolute Frequency Distribution
Depicting a Relative Frequency Distribution
Common Types of Histograms

APPLICATION 6.2 Deciding Authorship

APPLICATION 6.3 Quality Control in Manufacturing

6.8 FREQUENCY POLYGON AND FREQUENCY CURVE

The Frequency Polygon
The Frequency Curve

6.9 OGIVES

6.10 GRAPHING TWO VARIABLES

Scatter Diagrams
Time-Series Line Graphs

6.11 BAR CHARTS

6.12 PIE CHARTS

6.13 UNUSUAL GRAPHS

Statistical Maps
Pictograms
Stem-and-Leaf Diagrams

APPLICATION 6.4 How to Lie With Statistics

Box-and-Whisker Diagrams

7. Presenting Data: Summary Measures

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7.1 MAJOR TYPES OF SUMMARY MEASURES

Measures of Central Tendency
Measures of Dispersion
Measures of Shape
Summarizing Qualitative Data
Parameters and Statistics

7.2 THE ARITHMETIC MEAN

Calculation from Ungrouped Data
Symbolic Expression
Calculation from Grouped Data
The Nature of the Mean

7.3 THE MEDIAN

Calculation from Ungrouped Data
Symbolic Expression
Calculation from Grouped Data
Median Versus Mean

7.4 THE MODE

Calculation from Grouped Data
The Mode and the Frequency Curve

7.5 OTHER MEASURES OF CENTRAL TENDENCY

The Midrange
The Trimmed Mean
The Weighted Mean

7.6 MEASURES OF DISPERSION: AN OVERVIEW

7.7 THE RANGE

7.8 INTERFRACTILE RANGES

Interfractile Ranges Defined By Quartiles
Interfractile Ranges Defined By Deciles
Disadvantages of Distance Measures

7.9 THE MEAN ABSOLUTE DEVIATION

7.10 THE VARIANCE

Calculation from Ungrouped Data
Calculation from Grouped Data
Practical Problems

7.11 THE STANDARD DEVIATION

Describing the Normal Frequency Distribution
Applying Chebyshev's Theorem

APPLICATION 7.1 Standard Scores

APPLICATION 7.2 Control Charts

Comparing the Degree of Dispersion of Different Data Sets

APPLICATION 7.3 On the Accuracy of National Income Statistics

7.12 MEASURES OF SHAPE

Skewness
The Coefficient of Skewness
Kurtosis

7.13 THE PROPORTION

APPLICATION 7.4 The Safety of Anesthetics

APPLICATION 7.5 Networks Battle Nielsen

Part IV Probability Concepts: The Foundations of Inference

8. The Theory of Probability

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8.1 INTRODUCTION

8.2 BASIC PROBABILITY CONCEPTS

The Random Experiment
The Sample Space

8.3 THE NATURE OF RANDOM EVENTS

Simple Events
Composite Events

8.4 HOW RANDOM EVENTS RELATE TO EACH OTHER

Mutually Exclusive Events
Collectively Exhaustive Events
Complementary Events
Unions and Intersections
Venn Diagrams

8.5 ALTERNATIVE PROBABILITY CONCEPTS

Objective Probability: The Theoretical Approach
Objective Probability: The Empirical Approach
Subjective Probability

APPLICATION 8.1 The Incredible Hole-in-One Record of 1989

8.6 COUNTING TECHNIQUES

Factorials
Permutations

APPLICATION 8.2 The Magic Number Seven

Combinations

APPLICATION 8.3 The ESP Mystery

APPLICATION 8.4 Connecticut Lotto Chief Loses Job

8.7 LAWS OF PROBABILITY: ADDITION

The General Addition Law
The Special Addition Law

8.8 LAWS OF PROBABILITY: MULTIPLICATION

Unconditional Probability
Conditional Probability
Joint Probability
The General Multiplication Law

APPLICATION 8.5 The Miracle of the Matching Birthdays

Dependent Versus Independent Events
The Special Multiplication Law

APPLICATION 8.6 Probability in Court

8.9 PROBABILITY LAWS AND TREE DIAGRAMS

8.10 REVISING PROBABILITIES: BAYES' THEOREM

9. Discrete Probability Distributions

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9.1 BASIC CONCEPTS

The Random Variable
The Probability Distribution
Summary Measures for the Probability Distribution

9.2 THE BINOMIAL PROBABILITY DISTRIBUTION

The Bernoulli Process
The Binomial Formula
Binomial Summary Measures

9.3 THE BINOMIAL PROBABILITY DISTRIBUTION FAMILY

Meeting the Family
Binomial Probability Tables

APPLICATION 9.1 Budgeting Research and Development

APPLICATION 9.2 Acceptance Sampling Plans

Binomial Probabilities and Computer Programs
Pascal's Triangle

9.4 THE POISSON PROBABILITY DISTRIBUTION

The Poisson Process
The Poisson Formula
Poisson Summary Measures

9.5 THE POISSON PROBABILITY DISTRIBUTION FAMILY

Poisson Probability Tables

APPLICATION 9.3 Probability Applied to Anti-Aircraft Fire

Poisson Probabilities and Computer Programs

APPLICATION 9.4 Supplying Spare Parts to Polaris Submarines

9.6 THE HYPERGEOMETRIC PROBABILITY DISTRIBUTION

The Hypergeometric Formula

APPLICATION 9.5 Evidence of Sexism?

Hypergeometric Summary Measures

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Table of Contents Part II

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