Statistics - Gouri K. Bhattacharyya

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Résumé :

1 INTRODUCTION TO STATISTICS 1
1 The Subject and Scope of Statistics 2
2 Statistics in Aid of Scientific Inquiry 4
3 Two Basic Concepts-Population and Sample 6
4 The Purposeful Collection of Data 11
Case Study: Statistics in Context 12
5 Objectives of Statistics 14

2 ORGANIZATION AND DESCRIPTION OF DATA 17
1 Main Types of Data 18
2 Describing Data by Tables and Graphs 19
3 Measures of Center 31
4 Measures of Variation 37
5 Checking the Stability of the Observations over Time 47
6 More on Graphics 50
Case Study: Statistics in Context 52

3 DESCRIPTIVE STUDY OF BIVARIATE DATA 64
1 Summarization of Bivariate Categorical Data 65
2 A Designed Experiment for Making a Comparison 69
3 Scatter Diagram of Bivariate Measurement Data 70
4 The Correlation Coefficient-A Measure of Linear Relation 73
5 Prediction of One Variable from another (Linear Regression) 82

4 PROBABILITY 91
1 Probability of an Event 92
2 Methods of Assigning Probability 97
3 Event Operations and Two Laws of Probability 102
4 Conditional Probability and Independence 109
5 Bayes' Theorem 117
6 Random Sampling from a Finite Population 121
Case Study: Statistics in Context 126

5 PROBABILITY DISTRIBUTIONS 134
1 Random Variables 135
2 Probability Distribution of a Discrete Random Variable 138
3 Mean (Expected Value) and Standard Deviation of a Probability Distribution 144
4 Successes and Failures-Bernoulli Trials 150
5 The Binomial Distribution 154
6 The Poisson Distribution and Rare Events 165

6 THE NORMAL DISTRIBUTION 178
1 Probability Model for a Continuous Random Variable 179
2 The Normal Distribution-Its General Features 184
3 The Standard Normal Distribution 186
4 Probability Calculations with Normal Distributions 191
5 The Normal Approximation to the Binomial 194
6 Checking the Plausibility of a Normal Model 199
7 Transforming Observations to Attain Near Normality 202

7 VARIATION IN REPEATED SAMPLES-SAMPLING DISTRIBUTIONS 210
1 The Sampling Distribution of a Statistic 212
2 Distribution of the Sample Mean and the Central Limit Theorem 218
Case Study: Statistics in Context 228

8 DRAWING INFERENCES FROM LARGE SAMPLES 235
1 Two Types of Statistical Inference: Estimation and Testing 236
2 Point Estimation of a Population Mean 238
3 Confidence Interval Estimation of a Population Mean 242
4 Testing Hypotheses about a Population Mean 250
5 Inferences about a Population Proportion 261

9 SMALL SAMPLE INFERENCES FOR NORMAL POPULATIONS 278
1 Student's t Distribution 279
2 Inferences about ...

Biographie:
-Small Sample Size 282
3 Relationship between Tests and Confidence Intervals 289
4 Inferences about the Standard Deviation ...

Sommaire:

Statistics: Principles and Methods, 8th Edition provides students and business professionals with a comprehensive introduction to statistics concepts, terminology, and methods with a wide array of practical applications. Real-world data provides an easily relatable frame of reference, while numerous examples reinforce key ideas and demonstrate critical concepts to help ease student comprehension. Designed for those seeking a highly practical introduction to statistical measurement, reasoning, and analysis, this book requires no specific mathematical background and leaves derivations behind in favor of logic, reasoning, and modern statistics software.

Concepts are introduced first in a real-life setting to illustrate immediate relevancy, and are subsequently expanded to relate underlying mechanisms, limitations, and further applications. An emphasis on the relationship between validity and assumptions underscores the importance of critical thinking and the use of appropriate models while instilling thoughtful habits that lead to accuracy in interpretation. Going beyond the typical introductory text to keep the focus on application, this book gives students a deeper understanding of statistics as it is used every day across disciplines and industries.