Robert Gould,
Rebecca Wong,
Colleen Ryan
Essential Statistics -- ACCUMULATOR
Onbekend Engels 2020 3e druk 9780136570639Levertijd ongeveer 8 werkdagen
Gratis verzonden
Specificaties
ISBN13:9780136570639
Taal:Engels
Bindwijze:onbekend
Uitgever:Pearson Education (US)
Druk:3
Lezersrecensies
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Inhoudsopgave
Table of Contents
- Preface
- Index of Applications
- 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
- Data Project–How Are Data Stored?
- 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
- Data Project–Asking Questions
- 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
- Data Project–The Statistical Investigation Cycle
- Regression Analysis: Exploring Associations between Variables
- Case Study—Forecasting Home Prices
- 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
- Data Project–Data Moves
- 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
- Data Project–Submitting Data
- 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)
- Data Project–Generating Random Numbers
- 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
- Data Project–Population Proportions
- 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
- Data Project–Dates as Data
- Inferring Population Means
- Case Study—You Look Sick! Are You Sick?
- 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 Means
- 9.6 Overview of Analyzing Means
- Data Project–Data Structures
- Analyzing Categorical Variables and Interpreting Research
- Case Study—Popping Better Popcorn
- 10.1 The Basic Ingredients for Testing with Categorical Variables
- 10.2 Chi-Square Tests for Associations between Categorical Variables
- 10.3 Reading Research Papers
- Data Project–Think Small
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