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Analyzing Multivariate Data James Lattin

Analyzing Multivariate Data By James Lattin

Analyzing Multivariate Data by James Lattin


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Summary

Offering the latest teaching and practice of applied multivariate statistics, this text is designed for students who need an applied introduction to the subject.

Analyzing Multivariate Data Summary

Analyzing Multivariate Data by James Lattin

Offering the latest teaching and practice of applied multivariate statistics, this text is perfect for students who need an applied introduction to the subject. Lattin, Carroll, and Green have created a text that speaks to the needs of applied students who have advanced beyond the beginning level, but are not advanced statistics majors. The text provides a three-part structure. First, the authors begin each major topic by developing students' statistical intuition through applications. Then, they providing illustrative examples for support. Finally, for those courses where it will be valuable, they describe relevant mathematical underpinnings with vectors and matrix algebra. Additionally, each chapter follows a standard format. This format begins by discussing a general set of research objectives, followed by illustrative examples of problems in different areas. Then it provides an explanation of how each method works, followed by a sample problem, application of the technique, and interpretation of results.

Analyzing Multivariate Data Reviews

Part One: OVERVIEW. 1. Introduction. The Nature of Multivariate Data. Overview of Multivariate Methods. Format of Succeeding Chapters. 2. Vectors and Matrixes. Introduction. Definitions. Geometric Interpretation of Operations. Matrix Properties. Learning Summary. Exercises. Part Two: ANALYSIS OF INTERDEPENDENCE. 3. Regression Analysis. Introduction. Regression Analysis: How it Works. Sample Problem: Leslie Salt Property. Learning Summary. Exercises. 4. Principal Components Analysis. Introduction. Principal Components: How it Works. Sample Problem: Gross State Production. Questions Regarding the Application of Principal Components. Learning Summary. Exercises. 5. Exploratory Factor Analysis. Introduction. Exploratory Factor Analysis: How it Works. Sample Problem: Perceptions of Ready-to-Eat Cereals. Questions Regarding the Application of Factor Analysis. Learning Summary. Exercises. 6. Confirmatory Factor Analysis. Introduction. Confirmatory Factor Analysis: How Does it Work? Sample Problems. Questions Regarding the Application of Confirmatory Factor Analysis. Learning Summary. Exercises. 7. Multidimensional Scaling. Introduction. Metric MDS: How Does it Work? Non-Metric MDS: How Does it Work? Individual Differences Scaling: How Does It Work? Centroid Scaling: How Does it Work? A Note on Model Validation. Learning Summary. Exercises. 8. Clustering. Introduction. Objectives of Cluster Analysis. Measures of Distance, Dissimilarity, and Density. Agglomerative Clustering: How IT Works. Partitioning: How it Works. Sample Problem: Preference Segmentation. Questions Regarding the Application of Cluster Analysis. Learning Summary. Exercises. Part Three: ANALYSIS OF DEPENDENCE. 9. Canonical Correlation. Introduction. Canonical Correlation: How Does it Work? Sample Problem. Questions Regarding the Application of Canonical Correlation. Learning Summary. Exercises. 10. Structural Equation Models with Latent Variables. Introduction. Structural Equations with Latent Variables: How Does it Work? Sample Problem: Modeling the Adoption of Innovation. Questions Regarding the Application of Structural Equations with Latent Variables. Learning Summary. Exercises. 11. Analysis of Variance. Introduction. ANOLVA and ANCOVA: How Does it Work? Sample Problem: Test Marketing a New Product. Multiple Analysis of Variance (MANOVA): How Does it Work. Sample Problem: Testing Advertising Message Strategy. Questions Regarding the Application of MANOVA and MANCOVA. Learning Summary. Exercises. 12. Discriminant Analysis. Introduction. Two-Group Discriminant Analysis: How Does it Work? Sample Problem: Book Club Data. Questions Regarding the Application of Two-Group Discriminant Analysis. Multiple Discriminant Analysis: How Does it Work? Sample Problem: Real Estate. Questions Regarding the Application of Multiple Discriminant Analysis. Learning Summary. Exercises. 13. Logit Choice Models. Introduction. Binary Logit Model: How Does it Work? Sample Problem: Books Direct. Multinomial Logit Model: How Does it Work? Sample Problem: Brand Choice. Questions Regarding the Application of Logit Choice Models. Learning Summary. Exercises.

Table of Contents

Part One: OVERVIEW. 1. Introduction. The Nature of Multivariate Data. Overview of Multivariate Methods. Format of Succeeding Chapters. 2. Vectors and Matrixes. Introduction. Definitions. Geometric Interpretation of Operations. Matrix Properties. Learning Summary. Exercises. Part Two: ANALYSIS OF INTERDEPENDENCE. 3. Regression Analysis. Introduction. Regression Analysis: How it Works. Sample Problem: Leslie Salt Property. Learning Summary. Exercises. 4. Principal Components Analysis. Introduction. Principal Components: How it Works. Sample Problem: Gross State Production. Questions Regarding the Application of Principal Components. Learning Summary. Exercises. 5. Exploratory Factor Analysis. Introduction. Exploratory Factor Analysis: How it Works. Sample Problem: Perceptions of Ready-to-Eat Cereals. Questions Regarding the Application of Factor Analysis. Learning Summary. Exercises. 6. Confirmatory Factor Analysis. Introduction. Confirmatory Factor Analysis: How Does it Work? Sample Problems. Questions Regarding the Application of Confirmatory Factor Analysis. Learning Summary. Exercises. 7. Multidimensional Scaling. Introduction. Metric MDS: How Does it Work? Non-Metric MDS: How Does it Work? Individual Differences Scaling: How Does It Work? Centroid Scaling: How Does it Work? A Note on Model Validation. Learning Summary. Exercises. 8. Clustering. Introduction. Objectives of Cluster Analysis. Measures of Distance, Dissimilarity, and Density. Agglomerative Clustering: How IT Works. Partitioning: How it Works. Sample Problem: Preference Segmentation. Questions Regarding the Application of Cluster Analysis. Learning Summary. Exercises. Part Three: ANALYSIS OF DEPENDENCE. 9. Canonical Correlation. Introduction. Canonical Correlation: How Does it Work? Sample Problem. Questions Regarding the Application of Canonical Correlation. Learning Summary. Exercises. 10. Structural Equation Models with Latent Variables. Introduction. Structural Equations with Latent Variables: How Does it Work? Sample Problem: Modeling the Adoption of Innovation. Questions Regarding the Application of Structural Equations with Latent Variables. Learning Summary. Exercises. 11. Analysis of Variance. Introduction. ANOLVA and ANCOVA: How Does it Work? Sample Problem: Test Marketing a New Product. Multiple Analysis of Variance (MANOVA): How Does it Work. Sample Problem: Testing Advertising Message Strategy. Questions Regarding the Application of MANOVA and MANCOVA. Learning Summary. Exercises. 12. Discriminant Analysis. Introduction. Two-Group Discriminant Analysis: How Does it Work? Sample Problem: Book Club Data. Questions Regarding the Application of Two-Group Discriminant Analysis. Multiple Discriminant Analysis: How Does it Work? Sample Problem: Real Estate. Questions Regarding the Application of Multiple Discriminant Analysis. Learning Summary. Exercises. 13. Logit Choice Models. Introduction. Binary Logit Model: How Does it Work? Sample Problem: Books Direct. Multinomial Logit Model: How Does it Work? Sample Problem: Brand Choice. Questions Regarding the Application of Logit Choice Models. Learning Summary. Exercises.

Additional information

GOR006386095
9780534349745
0534349749
Analyzing Multivariate Data by James Lattin
Used - Very Good
Hardback
Cengage Learning, Inc
20021203
580
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in very good condition, but if you are not entirely satisfied please get in touch with us

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