Introduction to Statistical Methods and Data Analysis 6th edition

R. Lynam Ott and Michael T. Longnecker
Publisher: Cengage Learning

eBook

Access is contingent on use of this textbook in the instructor's classroom.

• Chapter 1: Statistics and the Scientific Method
• 1.1: Introduction (3)
• 1.2: Why Study Statistics?
• 1.3: Some Current Applications of Statistics
• 1.4: A Note to the Student
• 1.5: Summary
• 1.6: Exercises

• Chapter 2: Using Surveys and Experimental Studies to Gather Data
• 2.1: Introduction and Abstract of Research Study
• 2.2: Observational Studies
• 2.3: Sampling Designs for Surveys
• 2.4: Experimental Studies
• 2.5: Designs for Experimental Studies
• 2.6: Research Study: Exit Polls versus Election Results
• 2.7: Summary
• 2.8: Exercises

• Chapter 3: Data Description
• 3.1: Introduction and Abstract of Research Study
• 3.2: Calculators, Computers, and Software Systems
• 3.3: Describing Data on a Single Variable: Graphical Methods (3)
• 3.4: Describing Data on a Single Variable: Measures of Central Tendency (3)
• 3.5: Describing Data on a Single Variable: Measures of Variability (2)
• 3.6: The Boxplot
• 3.7: Summarizing Data from More Than One Variable: Graphs and Correlation
• 3.8: Research Study: Controlling for Student Background in the Assessment of Teaching
• 3.9: Summary and Key Formulas
• 3.10: Exercises (3)

• Chapter 4: Probability and Probability Distributions
• 4.1: Introduction and Abstract of Research Study
• 4.2: Finding the Probability of an Event
• 4.3: Basic Event Relations and Probability Laws
• 4.4: Conditional Probability and Independence
• 4.5: Bayes' Formula
• 4.6: Variables: Discrete and Continuous (1)
• 4.7: Probability Distributions for Discrete Random Variables
• 4.8: Two Discrete Random Variables: The Binomial and the Poisson
• 4.9: Probability Distributions for Continuous Random Variables
• 4.10: A Continuous Probability Distribution: The Normal Distribution (4)
• 4.11: Random Sampling
• 4.12: Sampling Distributions (3)
• 4.13: Normal Approximation to the Binomial
• 4.14: Evaluating Whether or Not a Population Distribution Is Normal
• 4.15: Research Study: Inferences about Performance-Enhancing Drugs among Athletes
• 4.16: Minitab Instructions
• 4.17: Summary and Key Formulas
• 4.18: Exercises (2)

• Chapter 5: Inferences about Population Central Values
• 5.1: Introduction and Abstract of Research Study (1)
• 5.2: Estimation of µ (1)
• 5.3: Choosing the Sample Size for Estimating µ (1)
• 5.4: A Statistical Test for µ
• 5.5: Choosing the Sample Size for Testing µ (1)
• 5.6: The Level of Significance of a Statistical Test
• 5.7: Inferences about u for a Normal Population, ω Unknown (3)
• 5.8: Inferences about µ When Population Is Nonnormal and n Is Small: Bootstrap Methods
• 5.9: Inferences about the median
• 5.10: Research Study: Percent Calories from Fat
• 5.11: Summary and Key Formulas
• 5.12: Exercises (3)

• Chapter 6: Inferences Comparing Two Population Central Values
• 6.1: Introduction and Abstract of Research Study
• 6.2: Inferences about µ12 ; Independent Samples (3)
• 6.3: A Nonparametric Alternative: The Wilcoxon Rank Sum Test (1)
• 6.4: Inferences about µ12 : Paired Data (2)
• 6.5: A Nonparametric Alternative: The Wilcoxon Signed-Rank Test (1)
• 6.6: Choosing Sample Sizes for Inferences about µ12
• 6.7: Research Study: Effects of Oil Spill on Plant Growth
• 6.8: Summary and Key Formulas
• 6.9: Exercises (3)

• Chapter 7: Inferences about population Variances
• 7.1: Introduction and Abstract of Research Study (1)
• 7.2: Estimation and Tests for a Population Variance
• 7.3: Estimation and Tests for Comparing Two Population Variances
• 7.4: Tests for Comparing t>2 Population Variances (2)
• 7.5: Research Study: Evaluation of Method for Detecting E. coli
• 7.6: Summary and Key Formulas
• 7.7; Exercises (4)

• Chapter 8: Inferences about more Than Two Population Central Values
• 8.1: Introduction and Abstract of Research Study (1)
• 8.2: A Statistical Test about More Than Two Population Means: An Analysis of Variance (1)
• 8.3: The Model for Observations in a Completely Randomized Design
• 8.4: Checking on the AOV Conditions
• 8.5: An Alternative Analysis: Transformations of the Data (1)
• 8.6: A Nonparametric Alternative: The Kruskal-Wallis Test (9)
• 8.7: Research Study: Effect of Timing on the Treatment of Port-Wine Stains with Lasers
• 8.8: Summary and Key Formulas
• 8.9: Exercises

• Chapter 9: Multiple Comparisons
• 9.1: Introduction and Abstract of Research Study
• 9.2: Linear Contrasts (2)
• 9.3: Which Error Rate is Controlled?
• 9.4: Fisher's Least Significant Difference
• 9.5: Turkey's W Procedure
• 9.6: Student-Newman-Keuls Procedure
• 9.7: Dunnett's Procedure: Comparison of Treatments to a Control
• 9.8: Scheffe's S Method
• 9.9: A Nonparametric Multiple-Comparison Procedure
• 9.10: Research Study: Are Interviewers' Decisions Affected by Different Handicap Types?
• 9.11: Summary and Key Formulas
• 9.12: Exercises (8)

• Chapter 10: Categorical Data
• 10.1: Introduction and Abstract of Research Study
• 10.2: Inferences about a Population Proportion π (4)
• 10.3: Inferences about the Difference between Two Population Proportions, π 1 - π 2 - (2)
• 10.4: Inferences about Several Proportions: Chi-Square Goodness-of-Fit Test
• 10.5: Contingency Tables: Tests for Independence and Homogeneity (2)
• 10.6: Measuring Strength of Relation
• 10.7: Odds and Odds Ratios
• 10.8: Combining Sets of 2 X 2 Contingency Tables
• 10.9: Research Study: Does Gender Bias Exist in the Selection of Students for Vocational Education?
• 10.10: Summary and Key Formulas
• 10.11: Exercises

• Chapter 11: Linear Regression and Correlation
• 11.1: Introduction and Abstract of Research Study
• 11.2: Estimating Model parameters
• 11.3: Inferences about Regression Parameters
• 11.4: Predicting new y Values Using Regression
• 11.5: Examining Lack of Fit in Linear Regression
• 11.6: The Inverse Regression Problem (Calibration)
• 11.7: Correlation
• 11.8: Research Study: Two Methods for Detecting E. coli
• 11.9: Summary and Key Formulas
• 11.10: Exercises

• Chapter 12: Multiple Regression and the General Linear Model
• 12.1: Introduction and Abstract of Research Study
• 12.2: The General Linear Model
• 12.3: Estimating Multiple Regression Coefficients
• 12.4: Inferences in Multiple Regression
• 12.5: Testing a Subset of Regression Coefficients
• 12.6: Forecasting Using Multiple Regression
• 12.7: Comparing the Slopes of Several Regression Lines
• 12.8: Logistic Regression
• 12.9: Some Multiple Regression Theory (Optional)
• 12.10: Research Study: Evaluation of the Performance of an Electric Drill
• 12.11: Summary and Key Formulas
• 12.12: Exercises

• Chapter 13: Further Regression Topics
• 13.1: Introduction and Abstract of Research Study
• 13.2: Selecting the Variables (Step 1)
• 13.3: Selecting the Variables (Step 2)
• 13.4: Checking Model Assumptions (Step 3)
• 13.5: Research Study: Construction Costs for Nuclear Power Plants
• 13.6: Summary and Key Formulas
• 13.7: Exercises

• Chapter 14: Analysis of Variance for Completely Randomized Designs
• 14.1: Introduction and Abstract of Research Study
• 14.2: Completely Randomized Design with a Single Factor
• 14.3: Factorial Treatment Structure
• 14.4: Factorial Treatment Structures with an Unequal Number of Replications
• 14.5: Estimation of Treatment Differences and Comparisons of Treatment Means
• 14.6: Determining the Number of Replications
• 14.7: Research Study: Development of a Low-Fat Processed Meat
• 14.8: Summary and Key Formulas
• 14.9: Exercises

• Chapter 15: Analysis of Variance for Blocked Designs
• 15.1: Introduction and Abstract of Research Study
• 15.2: Randomized Complete Block Design
• 15.3: Latin Square Design
• 15.4: Factorial Treatment Structure in a Randomized Complete Block Design
• 15.5: A Nonparametric Alternative - Friedman's Test
• 15.6: Research Study: Control of Leatherjackets
• 15.7: Summary and Key Formulas
• 15.8: Exercises

• Chapter 16: The Analysis of Covariance
• 16.1: Introduction and Abstract of Research Study
• 16.2: A Completely Randomized Design with One Covariate
• 16.3: The Extrapolation Problem
• 16.4: Multiple Covariates and More Complicated Designs
• 16.5: Research Study: Evaluation of Cool-Season Grasses for Putting Greens
• 16.6: Summary
• 16.7: Exercises

• Chapter 17: Analysis of Variance for Some Fixed-, Random-, and Mixed-Effects Models
• 17.1: Introduction and Abstract of Research Study
• 17.2: A One-Factor Experiment with Random Treatment Effects
• 17.3: Extensions of Random-Effects Models
• 17.4: Mixed-Effects Models
• 17.5: Rules for Obtaining Expected Mean Squares
• 17.6: Nested Factors
• 17.7: Research Study: Factors Affecting Pressure Drops Across Expansion Joints
• 17.8: Summary
• 17.9: Exercises

• Chapter 18: Split-Plot, Repeated Measures, and Crossover Designs
• 18.1: Introduction and Abstract of Research Study
• 18.2: Split-Plot Designed Experiments
• 18.3: Single-Factor Experiments with Repeated Measures
• 18.4: Two-Factor Experiments with Repeated Measures on One of the Factors
• 18.5: Crossover Designs
• 18.6: Research Study: Effects of Oil Spill on Plant Growth
• 18.7: Summary
• 18.8: Exercises

• Chapter 19: Analysis of Variance for Some Unbalanced Designs
• 19.1: Introduction and Abstract of Research Study
• 19.2: A Randomized Block Design with One or More Missing Observations
• 19.3: A Latin Square Design with Missing Data
• 19.4: Balanced Incomplete Block (BIB) Designs
• 19.5: Research Study: Evaluation of the Consistency of Property Assessments
• 19.6: Summary and Key Formulas
• 19.7: Exercises

Questions Available within WebAssign

Most questions from this textbook are available in WebAssign. The online questions are identical to the textbook questions except for minor wording changes necessary for Web use. Whenever possible, variables, numbers, or words have been randomized so that each student receives a unique version of the question. This list is updated nightly.

Question Availability Color Key
BLACK questions are available now
GRAY questions are under development

Group Quantity Questions
Chapter 1: Statistics and the Scientific Method
1.E 3 001 004 005
Chapter 2: Using Surveys and Experimental Studies to Gather Data
2 0
Chapter 3: Data Description
3.E 11 004 007 011 015 016 021 029 031 043 048 077
Chapter 4: Probability and Probability Distributions
4.E 10 036 065 069 070 072 080 082 086 101 114
Chapter 5: Inferences about Population Central Values
5.E 10 003 005 015 025 043 045 046 063 072 077
Chapter 6: Inferences Comparing Two Population Central Values
6.E 10 005 006 011 017 025 029 035 042 044 047
Chapter 7: Inferences about population Variances
7.E 7 001 020 022 025 029 033 034
Chapter 8: Inferences about more Than Two Population Central Values
8.E 12 001 006 019 023 026 027 029 030 035 036 039 040
Chapter 9: Multiple Comparisons
9.E 10 005 007 012 013 014 017 018 023 024 025
Chapter 10: Categorical Data
10.E 8 006 007 013 015 019 024 040 042
Chapter 11: Linear Regression and Correlation
11 0
Chapter 12: Multiple Regression and the General Linear Model
12 0
Chapter 13: Further Regression Topics
13 0
Chapter 14: Analysis of Variance for Completely Randomized Designs
14 0
Chapter 15: Analysis of Variance for Blocked Designs
15 0
Chapter 16: The Analysis of Covariance
16 0
Chapter 17: Analysis of Variance for Some Fixed-, Random-, and Mixed-Effects Models
17 0
Chapter 18: Split-Plot, Repeated Measures, and Crossover Designs
18 0
Chapter 19: Analysis of Variance for Some Unbalanced Designs
19 0
Chapter 20
20 0
Total 81