| 000 -LEADER |
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| fixed length control field |
nam a22 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
231001b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780135258521 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
658.8342 |
| Item number |
ROD |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Rodrigues, Joanne |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Product analytics : applied data science techniques for actionable consumer rights |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher, distributor, etc |
Addison Wesley, |
| Date of publication, distribution, etc |
2021 |
| Place of publication, distribution, etc |
Boston : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxii, 417 p. ; |
| Other physical details |
ill., |
| Dimensions |
23 cm |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
4122.18 |
| Price type code |
INR |
| Unit of pricing |
01 |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
Pearson business analytics series |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Product Analytics bridges the divide between high-value business insights and today’s best statistics and machine learning techniques, offering practical qualitative and quantitative techniques to generate actionable insight into customer behavior. Experienced data scientist and enterprise manager Joanne Rodrigues-Craig presents statistical techniques to determine why things happen, and how to change what people do at scale. She complements these with the social sciences’ most useful qualitative techniques for creating better theories, designing better metrics, and driving more rapid and sustained behavior change. You’ll learn through intuitive examples from both web products and “real life,” including numeric examples illuminating hypothesis testing, regression, and other statistical techniques. Discover how to: Think like a social scientist to contextualize individual behavior in social environments, explore how human behavior develops, and establish the conditions for change Develop core metrics and effective KPIs for user analytics in any web product Understand statistical inference, the differences between correlation and causation and when to apply each technique Conduct more effective A/B tests Build intuitive predictive models to capture user behavior in product Using the latest quasi-experimental design techniques and statistical matching tease out causal effects from observational data Implement sophisticated targeting methods like uplift modeling for marketing campaigns Project business costs/subgroup population changes by using advanced demographic projection methods Do all this in R. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Machine learning |
|
|---|
| Topical term or geographic name as entry element |
Big data |
|
|---|
| Topical term or geographic name as entry element |
Business enterprises Data processing |
|
|---|
| Topical term or geographic name as entry element |
Consumer Behavior |
|
|---|
| Topical term or geographic name as entry element |
Information visualization |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Books |