{
"item_title" : "Python for Marketing Research and Analytics",
"item_author" : [" Jason S. Schwarz", "Chris Chapman", "Elea McDonnell Feit "],
"item_description" : "Part I: Basics of Python.- Chapter 1: Welcome to Python.- Chapter 2: The Python Language.- Part II Fundamentals of Data Analysis.- Chapter 3: Describing Data.- Chapter 4: Relationships Between Continuous Variables.- Chapter 5: Comparing Groups: Tables and Visualizations.- Chapter 6: Comparing Groups: Statistical Tests.- Chapter 7: Identifying Drivers of Outcomes: Linear Models.- Chapter 8: Additional Linear Modeling Topics.- Part III Advanced data analysis.- Chapter 9: Reducing Data Complexity.- Chapter 10: Segmentation: Unsupervised Clustering Methods for Exploring Subpopulations.- Chapter 11: Classification: Assigning observations to known categories.- Chapter 12: Conclusion.- Index.",
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Python for Marketing Research and Analytics
Overview
Part I: Basics of Python.- Chapter 1: Welcome to Python.- Chapter 2: The Python Language.- Part II Fundamentals of Data Analysis.- Chapter 3: Describing Data.- Chapter 4: Relationships Between Continuous Variables.- Chapter 5: Comparing Groups: Tables and Visualizations.- Chapter 6: Comparing Groups: Statistical Tests.- Chapter 7: Identifying Drivers of Outcomes: Linear Models.- Chapter 8: Additional Linear Modeling Topics.- Part III Advanced data analysis.- Chapter 9: Reducing Data Complexity.- Chapter 10: Segmentation: Unsupervised Clustering Methods for Exploring Subpopulations.- Chapter 11: Classification: Assigning observations to known categories.- Chapter 12: Conclusion.- Index.
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Details
- ISBN-13: 9783030497224
- ISBN-10: 3030497224
- Publisher: Springer
- Publish Date: November 2021
- Dimensions: 11 x 8.25 x 0.6 inches
- Shipping Weight: 1.43 pounds
- Page Count: 272
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