dimanche 12 mai 2019

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Statistics: Informed Decisions Using Data

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Table of Contents

(NOTE: Each chapter ends with Chapter Review and Consumer Reports Project.)

1. Data Collection.

Introduction to the Practice of Statistics. Observational Studies; Simple Random Sampling. Other Types of Sampling. Sources of Error in Sampling. The Design of Experiments. Case Study: Chrysalises for Cash. Decisions: What Movie Should I Go To?



2. Organizing and Summarizing Data.

Organizing Qualitative Data. Organizing Quantitative Data, I. Organizing Quantitative Data , II. Graphical Misrepresentations of Data. Case Study: The Day the Sky Roared. Decisions: Tables or Graphs?



3. Numerically Summarizing Data.

Measures of Central Tendency. Measures of Dispersion. Computing Measures of Central Tendency and Dispersion from Grouped Data. Measures of Position. The Five-Number Summary; Boxplots. Case Study: Who Was “A Mourner”? Decisions: What Car Should I Buy?



4. Describing the Relation Between Two Variables.

Scatter Diagrams; Linear Correlation. Least-squares Regression. Diagnostics on the Least-squares Regression Line. Nonlinear Regression: Transformations. Case Study: The Mystery of Global Temperature Change. Decisions: What Car Should I Buy?



5. Probability.

Probability of Simple Events. The Addition Rule; Complements. The Multiplication Rule. Conditional Probability. Counting Techniques. Case Study: The Case of the Body in the Bag. Decisions: Sports Probabilities.



6. Discrete Probability Distributions.

Probability Distributions. The Binomial Probability Distribution. The Poisson Probability Distribution. Case Study: The Voyage of the St. Andrew. Decisions: Should We Convict?



7. The Normal Probability Distribution.

Properties of the Normal Distribution. The Standard Normal Distribution. Applications of the Normal Distribution. Assessing Normality. Sampling Distributions; The Central Limit Theorem. The Normal Approximation to the Binomial Probability Distribution. Case Study: A Tale of Blood, Chemistry, and Health. Decisions: Join the Club.



8. Confidence Intervals about a Single Parameter.

Confidence Intervals about a Population Mean, ¿¿ known. Confidence Intervals about a Population Mean, ¿¿ unknown. Confidence Intervals about the Population Proportion. Confidence Intervals about a Population Standard Deviation. Case Study: The Search for a Fire-Safe Cigarette. Decisions: What's Your Major?



9. Hypothesis Testing.

The Language of Hypothesis Testing. Testing a Hypothesis about ¿¿, ¿¿ known. Testing a Hypothesis about ¿¿, ¿¿ unknown. Testing a Hypothesis about the Population Proportion. Testing a Hypothesis about ¿¿. The Probability of a Type II Error; the Power of the Test. Case Study: Dating Stonehenge. Decisions: What Does It Really Weigh?



10. Comparing Two Population Parameters.

Inference about Two Means: Dependent Samples. Inference about Two Means: Independent Samples. Inference about Two Population Proportions. Inference about Two Population Standard Deviations. Case Study: Control in the Design of an Experiment. Decisions: Where Should I Invest?



11. Chi-Square Procedures.

Chi-Square Goodness of Fit Test. Contingency Tables; Association. Chi-Square Test for Independence; Homogeneity of Proportions. Case Study: Feeling Lucky? Well, Are You? Decisions: Benefits of College.



12. Inference on the Least-squares Regression Model; ANOVA.

Inference about the Least-squares Regression Model. Confidence and Prediction Intervals. One-way Analysis of Variance. Case Study: Craniometry: Hat Size and Intelligence. Decisions: Buying a Car.



13. Nonparametric Statistics.

An Overview of Nonparametric Statistics. Runs Test for Randomness. Inferences about Measures of Central Tendency. Inferences about the Difference between Two Measures of Central Tendency: Dependent Samples. Inferences about the Difference between Two Measures of Central Tendency: Independent Samples. Spearman Rank Correlation Coefficient. Kruskal-Wallis Test. Case Study: Evaluating Alabama's 1891 House Bill 504. Decisions: Where Should I Live?

Get Statistics: Informed Decisions Using Data by Michael Sullivan, III, Joliet Junior College

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