Essential statistics : exploring the world through data /: exploring the world through data. ([2017])
- Record Type:
- Book
- Title:
- Essential statistics : exploring the world through data /: exploring the world through data. ([2017])
- Main Title:
- Essential statistics : exploring the world through data
- Further Information:
- Note: Robert Gould, University of California, Los Angeles, Colleen Ryan, California Lutheran University, Rebecca Wong, West Valley College.
- Other Names:
- Gould, Robert, 1965-
Ryan, Colleen N (Colleen Nooter), 1939-
Wong, Rebecca (Rebecca Kimmae) - Contents:
- Preface Index of Applications 1. Introduction to Data Case Study–Deadly Cell Phones? 1.1 What Are Data? 1.2 Classifying and Storing Data 1.3 Organizing Categorical Data 1.4 Collecting Data to Understand Causality Exploring Statistics–Collecting a Table of Different Kinds of Data 2. Picturing Variation with Graphs Case Study–Student-to-Teacher Ratio at Colleges 2.1 Visualizing Variation in Numerical Data 2.2 Summarizing Important Features of a Numerical Distribution 2.3 Visualizing Variation in Categorical Variables 2.4 Summarizing Categorical Distributions 2.5 Interpreting Graphs Exploring Statistics–Personal Distance 3. Numerical Summaries of Center and Variation Case Study–Living in a Risky World 3.1 Summaries for Symmetric Distributions 3.2 What's Unusual? The Empirical Rule and z-Scores 3.3 Summaries for Skewed Distributions 3.4 Comparing Measures of Center 3.5 Using Boxplots for Displaying Summaries Exploring Statistics–Does Reaction Distance Depend on Gender? 4. Regression Analysis: Exploring Associations between Variables Case Study–Catching Meter Thieves 4.1 Visualizing Variability with a Scatterplot 4.2 Measuring Strength of Association with Correlation 4.3 Modeling Linear Trends 4.4 Evaluating the Linear Model Exploring Statistics–Guessing the Age of Famous People 5. Modeling Variation with Probability Case Study–SIDS or Murder? 5.1 What Is Randomness? 5.2 Finding Theoretical Probabilities 5.3 Associations in Categorical Variables 5.4 Finding EmpiricalPreface Index of Applications 1. Introduction to Data Case Study–Deadly Cell Phones? 1.1 What Are Data? 1.2 Classifying and Storing Data 1.3 Organizing Categorical Data 1.4 Collecting Data to Understand Causality Exploring Statistics–Collecting a Table of Different Kinds of Data 2. Picturing Variation with Graphs Case Study–Student-to-Teacher Ratio at Colleges 2.1 Visualizing Variation in Numerical Data 2.2 Summarizing Important Features of a Numerical Distribution 2.3 Visualizing Variation in Categorical Variables 2.4 Summarizing Categorical Distributions 2.5 Interpreting Graphs Exploring Statistics–Personal Distance 3. Numerical Summaries of Center and Variation Case Study–Living in a Risky World 3.1 Summaries for Symmetric Distributions 3.2 What's Unusual? The Empirical Rule and z-Scores 3.3 Summaries for Skewed Distributions 3.4 Comparing Measures of Center 3.5 Using Boxplots for Displaying Summaries Exploring Statistics–Does Reaction Distance Depend on Gender? 4. Regression Analysis: Exploring Associations between Variables Case Study–Catching Meter Thieves 4.1 Visualizing Variability with a Scatterplot 4.2 Measuring Strength of Association with Correlation 4.3 Modeling Linear Trends 4.4 Evaluating the Linear Model Exploring Statistics–Guessing the Age of Famous People 5. Modeling Variation with Probability Case Study–SIDS or Murder? 5.1 What Is Randomness? 5.2 Finding Theoretical Probabilities 5.3 Associations in Categorical Variables 5.4 Finding Empirical Probabilities Exploring Statistics–Let's Make a Deal: Stay or Switch? 6. Modeling Random Events: The Normal and Binomial Models Case Study–You Sometimes Get More Than You Pay For 6.1 Probability Distributions Are Models of Random Experiments 6.2 The Normal Model 6.3 The Binomial Model (optional) Exploring Statistics–ESP with Coin Flipping 7. Survey Sampling and Inference Case Study–Spring Break Fever: Just What the Doctors Ordered? 7.1 Learning about the World through Surveys 7.2 Measuring the Quality of a Survey 7.3 The Central Limit Theorem for Sample Proportions 7.4 Estimating the Population Proportion with Confidence Intervals 7.5 Comparing Two Population Proportions with Confidence Exploring Statistics–Simple Random Sampling Prevents Bias 8. Hypothesis Testing for Population Proportions Case Study–Dodging the Question 8.1 The Essential Ingredients of Hypothesis Testing 8.2 Hypothesis Testing in Four Steps 8.3 Hypothesis Tests in Detail 8.4 Comparing Proportions from Two Populations Exploring Statistics–Identifying Flavors of Gum through Smell 9. Inferring Population Means Case Study–Epilepsy Drugs and Children 9.1 Sample Means of Random Samples 9.2 The Central Limit Theorem for Sample Means 9.3 Answering Questions about the Mean of a Population 9.4 Hypothesis Testing for Means 9.5 Comparing Two Population. … (more)
- Edition:
- Second edition
- Publisher Details:
- Boston : Pearson
- Publication Date:
- 2017
- Extent:
- 1 online resource (582 pages, 39 variously numbered pages ), color illustrations
- Subjects:
- 519.5
Mathematical statistics
Statistics
Mathematical statistics
Statistics
MATHEMATICS / Applied
MATHEMATICS / Probability & Statistics / General
Electronic books - Languages:
- English
- ISBNs:
- 9781292161280
1292161280 - Related ISBNs:
- 0134134400
9780134134406
0134133358
9780134133355
9780134466019
0134466012 - Notes:
- Note: Print version record.
- Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.725632
- Ingest File:
- 14_048.xml