Produktbild: Statistics: The Art and Science of Learning from Data, Global Edition

Statistics: The Art and Science of Learning from Data, Global Edition The Art and Science of Learning from Data, Global Edition

101,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

15.09.2022

Verlag

Pearson Studium

Seitenzahl

880

Maße (L/B/H)

27,4/21,2/3,1 cm

Gewicht

1856 g

Auflage

5

Sprache

Englisch

ISBN

978-1-292-44476-5

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

15.09.2022

Verlag

Pearson Studium

Seitenzahl

880

Maße (L/B/H)

27,4/21,2/3,1 cm

Gewicht

1856 g

Auflage

5

Sprache

Englisch

ISBN

978-1-292-44476-5

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: GPSR Kontakt

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  • Produktbild: Statistics: The Art and Science of Learning from Data, Global Edition
  • PART I: GATHERING AND EXPLORING DATA
    1. Statistics: The Art and Science of Learning from Data
      • Using Data to Answer Statistical Questions
      • Sample Versus Population
      • Organizing Data, Statistical Software, and the New Field of Data Science
      • Chapter Summary
      • Chapter Exercises
    2. Exploring Data with Graphs and Numerical Summaries
      • Different Types of Data
      • Graphical Summaries of Data
      • Measuring the Center of Quantitative Data
      • Measuring the Variability of Quantitative Data
      • Using Measures of Position to Describe Variability
      • Linear Transformations and Standardizing
      • Recognizing and Avoiding Misuses of Graphical Summaries
      • Chapter Summary
      • Chapter Exercises
    3. Exploring Relationships Between Two Variables
      • The Association Between Two Categorical Variables
      • The Relationship Between Two Quantitative Variables
      • Linear Regression: Predicting the Outcome of a Variable
      • Cautions in Analyzing Associations
      • Chapter Summary
      • Chapter Exercises
    4. Gathering Data
      • Experimental and Observational Studies
      • Good and Poor Ways to Sample
      • Good and Poor Ways to Experiment
      • Other Ways to Conduct Experimental and Nonexperimental Studies
      • Chapter Summary
      • Chapter Exercises
    PART II: PROBABILITY, PROBABILITY DISTRIBUTIONS, AND SAMPLINGDISTRIBUTIONS
    1. Probability in Our Daily Lives
      • How Probability Quantifies Randomness
      • Finding Probabilities
      • Conditional Probability
      • Applying the Probability Rules
      • Chapter Summary
      • Chapter Exercises
    2. Random Variables and Probability Distributions
      • Summarizing Possible Outcomes and Their Probabilities
      • Probabilities for Bell-Shaped Distributions
      • Probabilities When Each Observation Has Two Possible Outcomes
      • Chapter Summary
      • Chapter Exercises
    3. Sampling Distributions
      • How Sample Proportions Vary Around the Population Proportion
      • How Sample Means Vary Around the Population Mean
      • Using the Bootstrap to Find Sampling Distributions
      • Chapter Summary
      • Chapter Exercises
    PART III: INFERENTIAL STATISTICS
    1. Statistical Inference: Confidence Intervals
      • Point and Interval Estimates of Population Parameters
      • Confidence Interval for a Population Proportion
      • Confidence Interval for a Population Mean
      • Bootstrap Confidence Intervals
      • Chapter Summary
      • Chapter Exercises
    2. Statistical Inference: Significance Tests About Hypotheses
      • Steps for Performing a Significance Test
      • Significance Tests About Proportions
      • Significance Tests About a Mean
      • Decisions and Types of Errors in Significance Tests
      • Limitations of Significance Tests
      • The Likelihood of a Type II Error
      • Chapter Summary
      • Chapter Exercises
    3. Comparing Two Groups
      • Categorical Response: Comparing Two Proportions
      • Quantitative Response: Comparing Two Means
      • Comparing Two Groups with Bootstrap or Permutation Resampling
      • Analyzing Dependent Samples
      • Adjusting for the Effects of Other Variables
      • Chapter Summary
      • Chapter Exercises
    PART IV: ANALYZING ASSOCIATION AND EXTENDED STATISTICALMETHODS
    1. Analyzing the Association Between Categorical Variables
      • Independence and Dependence (Association)
      • Testing Categorical Variables for Independence
      • Determining the Strength of the Association
      • Using Residuals to Reveal the Pattern of Association
      • Fisher's Exact and Permutation Tests
      • Chapter Summary
      • Chapter Exercises
    2. Analyzing the Association Between Quantitative Variables: Regression Analysis
      • Modeling How Two Variables Are Related
      • Inference About Model Parameters and the Association
      • Describing the Strength of Association
      • How the Data Vary Around the Regression Line
      • Exponential Regression: A Model for Nonlinearity
      • Chapter Summary
      • Chapter Exercises
    3. Multiple Regression
      • Using Several Variables to Predict a Response
      • Extending the Correlation and R2 for Multiple Regression
      • Using Multiple Regression to Make Inferences
      • Checking a Regression Model Using Residual Plots
      • Regression and Categorical Predictors
      • Modeling a Categorical Response
      • Chapter Summary
      • Chapter Exercises
    4. Comparing Groups: Analysis of Variance Methods
      • One-Way ANOVA: Comparing Several Means
      • Estimating Differences in Groups for a Single Factor
      • Two-Way ANOVA
      • Chapter Summary
      • Chapter Exercises
    5. Nonparametric Statistics
      • Compare Two Groups by Ranking
      • Nonparametric Methods for Several Groups and for Matched Pairs
      • Chapter Summary
      • Chapter Exercises
    • Appendix
    • Answers
    • Index
    • Index of Applications
    • Credits