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ISBN-10 : 0534394027
ISBN-13 : 9780534394028
Author: Jessica M. Utts
PART 1: FINDING DATA IN LIFE.
1. The Benefits and Risks of Using Statistics. Statistics. Detecting Patterns and Relationships. Don''t Be Deceived by Improper Use of Statistics. Summary and Conclusions.
2. Reading the News.The Educated Consumer of Data. Origins of News Stories. How to be a Statistics Sleuth: Seven Critical Components. Four Hypothetical Examples of Bad Reports. Planning Your Own Study: Defining the Components in Advance.
3. Measurements, Mistakes, and Misunderstandings.Simple Measures Don''t Exist. It''s All in the Wording. Open or Closed Questions: Should Choices Be Given? Defining What is Being Measured. Defining a Common Language.
4. How to Get a Good Sample.Common Research Strategies. Defining a Common Language. The Beauty of Sampling. Simple Random Sampling. Other Sampling Methods. Difficulties and Disasters in Sampling.
5. Experiments and Observational Studies.Defining a Common Language. Designing a Good Experiment. Difficulties and Disasters in Experiments. Designing a Good Observational Experiment. Difficulties and Disasters in Observational Studies. Random Sample versus Random Assignment.
6. Getting the Big Picture.Final Questions. Case Studies.
PART 2: FINDING LIFE IN DATA.
7. Summarizing and Displaying Measurement Data.Turning Data into Information. Picturing Data: Stemplots and Histograms. Five Useful Numbers: A Summary. Boxplots. Traditional Measures: Mean, Variance, and Standard Deviation. Caution: Being Average Isn''t Normal.
8. Bell-Shaped Curves and Other Shapes.Populations, Frequency Curves, and Proportions. The Pervasiveness of Normal Curves. Percentiles and Standardized Scores. z-Scores and Familiar Intervals.
9. Plots, Graphs, and Pictures.Well-Designed Statistical Pictures. Pictures of Categorical Data. Pictures of Measurement Variables. Difficulties and Disasters in Plots, Graphs, and Pictures. A Checklist for Statistical Procedures.
10. Relationships Between Measurement Variables.Statistical Relationships. Strength versus Statistical Significance. Measuring Strength Through Correlation. Specifying Linear Relationships through Regression.
11. Relationships Can Be Deceiving.Illegitimate Correlations. Legitimate Correlation Does Not Imply Causation. Some Reasons for Relationships Between Variables. Confirming Causation.
12. Relationships Between Categorical Variables
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