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Full Description
Designed to teach students to apply statistical methods to real problems (a universal need), Bruce Trumbo's concise new book teaches basic statistical principles through their application to real data. The data sets are chosen from fields to which all students can relate, such as marketing, industrial safety, anthropology, psychology, banking, biology, linguistics, public health, geography, physics, sports, geology, and medicine. Throughout the book, the emphasis is on how statistical ideas and methods can be used to illuminate the data, rather than on how the data can be used to illustrate particular statistical methods. Some of the basic statistical methods that prove to be useful include graphical displays, confidence intervals, one and two-sample t-tests, chi-squared analyses of contingency tables, simple and multiple linear regression, correlation, one-way ANOVAs, and block designs. For each data set, students are guided through some basic procedures, usually using MINITAB[trademark], then invited to explore the data more extensively on their own, with answers and possible approaches.
Contents
1. LOOK BEFORE YOU LEAP (Role of Descriptive Methods in Data Analysis). Introduction. Population Densities of the 50 States. California Earthquakes. Heights of Students. The Speed of Light. 2. TASTING CHOCOLATE PUDDING (Paired Data and Blocking). Introduction. Are the Experts' Ratings to Be Trusted? A Statistical Test. Nonparametric Tests. Using a Block Design to Look at All Six Brands Together. Nesting Brands within Two Types of Pudding. 3. LEAD Showing Exposure to Lead. Formal Confirmation of Statistically Significant Exposure. Are Neighborhood and Age Important? Are Parental Exposure and Hygiene Important? 4. MEASURING A PERSON'S HEIGHT (Paired-t Methods, ANOVA). Introduction. Precision of the Height Measurements. Accuracy of the Height Measurements. Confirmatory Tests of Hypothesis. The Analysis of Variance. 5. Methods. A Test of Hypothesis and a Confidence Interval. The Issue of Practice. A Partially Hierarchical Experimental Design. 6. INTEREST RATES ON SAVINGS (Basic Nonparametric Methods). Introduction. Did S&Ls Give Higher Interest than Banks? Were Rates Higher for 1-year CDs than for 6-month CDs? Introduction. Descriptive Methods. An Analysis of Variance. Diagnosis of the ANOVA Model and Design. 8. MEASURING SEPARATION BETWEEN GROUPS. Introduction. Descriptive Methods. The Two-Sample t Statistics as a Measure of Separation Between Groups. A Multivariate Approach. Including a Third Species. Linear Discriminant Functions. 9. ELEMENTARY, MY DEAR STATISTICIAN (Chi-Squared Contingency Tables). Introduction. Do Uses of the Distinguish Among Writing Styles? Is the Imitation Detectable? 10. SMOKING AND SURVIVAL. Introduction. Summary Table for Smoking and Survival. A Statistical Test of Association. The Importance of Stratification. Standardized Mortality Ratios. A Simulation to Evaluate Yates' Correction. 11. CORRELATION DOES NOT IMPLY CAUSATION (4 Observational Studies). Introduction. Heart Disease, Diet and Telephones. European Rainfall. Calories and Sodium in Hot Dogs. Rainfall and High School Prediction, Serial Correlation). Introduction. Two Kinds of Eruptions. Using Regression to Predict the Time of the Next Eruption. Regression Assumptions and Regression Diagnostics. Using Multiple Regression to Predict Waiting (Regression for Modeling, Diagnostics). Introduction. Times on the Ground and in the Air. The Need to Take Direction of Travel Into Account. A Multiple Introduction. Comparing the HemoCue Machine with the Hospital Lab. Formal Inference Should the HemoCue Machine Be Used? Correlation and Regression
