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Causal inference : the mixtape / / Scott Cunningham
| Causal inference : the mixtape / / Scott Cunningham |
| Autore | Cunningham Scott |
| Pubbl/distr/stampa | New Haven, Connecticut : , : Yale University Press, , [2021] |
| Descrizione fisica | 1 online resource (352 pages) : illustrations |
| Disciplina | 501 |
| Soggetto topico |
Causation
Inference analysis of causes social sciences information analysis |
| ISBN |
9780300255881
0-300-25588-8 9780300251685 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | What Is Causal Inference? -- Do Not Confuse Correlation with Causality -- OptimizationMakes Everything Endogenous -- Example: Identifying Price Elasticity of Demand -- Conclusion -- Probability and Regression Review -- Directed Acyclic Graphs -- Introduction -- Introduction to DAG Notation -- Potential Outcomes Causal Model -- Introduction -- Physical Randomization -- Randomization Inference -- Conclusion -- Matching and Subclassification -- Subclassification -- Exact Matching -- Approximate Matching -- Regression Discontinuity -- Huge Popularity of Regression Discontinuity -- Estimation Using an RDD -- Challenges to Identification -- Replicating a Popular Design: The Close Election -- Regression Kink Design -- Conclusion -- Instrumental Variables -- History of Instrumental Variables: Father and Son -- Intuition of Instrumental Variables -- Homogeneous Treatment Effects -- Parental Methamphetamine Abuse and Foster Care -- The Problem of Weak Instruments -- Heterogeneous Treatment Effects -- Applications -- Popular IV Designs -- Conclusion -- Panel Data -- DAG Example -- Estimation -- Data Exercise: Survey of Adult Service Providers -- Conclusion -- Difference-in-Differences -- John Snow’s Cholera Hypothesis -- Estimation -- Inference -- Providing Evidence for Parallel Trends Through Event Studies and Parallel Leads -- The Importance of Placebos in DD -- Twoway Fixed Effects with Differential Timing -- Conclusion -- Synthetic Control -- Introducing the Comparative Case Study -- Prison Construction and Black Male Incarceration -- Conclusion. |
| Record Nr. | UNINA-9910554223803321 |
Cunningham Scott
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| New Haven, Connecticut : , : Yale University Press, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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SQL for data scientists : a beginner's guide for building datasets for analysis / / Renee M. Teate
| SQL for data scientists : a beginner's guide for building datasets for analysis / / Renee M. Teate |
| Autore | Teate Renee M. |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2021] |
| Descrizione fisica | 1 online resource (291 pages) |
| Disciplina | 005.756 |
| Soggetto topico |
SQL (Computer program language)
software data science information analysis text and data mining programming language |
| ISBN |
1-119-66939-1
1-119-66938-3 1-119-66937-5 9781119669364 9781119669371 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cover -- Title Page -- Copyright Page -- About the Author -- About the Technical Editor -- Acknowledgments -- Contents at a Glance -- Contents -- Introduction -- Who I Am and Why I'm Writing About This Topic -- Who This Book Is For -- Why You Should Learn SQL if You Want to Be a Data Scientist -- What I Hope You Gain from This Book -- Conventions -- Reader Support for This Book -- Companion Download Files -- How to Contact the Publisher -- How to Contact the Author -- Chapter 1 Data Sources -- Data Sources -- Tools for Connecting to Data Sources and Editing SQL -- Relational Databases -- Dimensional Data Warehouses -- Asking Questions About the Data Source -- Introduction to the Farmer's Market Database -- A Note on Machine Learning Dataset Terminology -- Exercises -- Chapter 2 The SELECT Statement -- The SELECT Statement -- The Fundamental Syntax Structure of a SELECT Query -- Selecting Columns and Limiting the Number of Rows Returned -- The ORDER BY Clause: Sorting Results -- Introduction to Simple Inline Calculations -- More Inline Calculation Examples: Rounding -- More Inline Calculation Examples: Concatenating Strings -- Evaluating Query Output -- SELECT Statement Summary -- Exercises Using the Included Database -- Chapter 3 The WHERE Clause -- The WHERE Clause -- Filtering SELECT Statement Results -- Filtering on Multiple Conditions -- Multi-Column Conditional Filtering -- More Ways to Filter -- BETWEEN -- IN -- LIKE -- IS NULL -- A Warning About Null Comparisons -- Filtering Using Subqueries -- Exercises Using the Included Database -- Chapter 4 CASE Statements -- CASE Statement Syntax -- Creating Binary Flags Using CASE -- Grouping or Binning Continuous Values Using CASE -- Categorical Encoding Using CASE -- CASE Statement Summary -- Exercises Using the Included Database -- Chapter 5 SQL JOINs -- Database Relationships and SQL JOINs -- A Common Pitfall when Filtering Joined Data -- JOINs with More than Two Tables -- Exercises Using the Included Database -- Chapter 6 Aggregating Results for Analysis -- GROUP BY Syntax -- Displaying Group Summaries -- Performing Calculations Inside Aggregate Functions -- MIN and MAX -- COUNT and COUNT DISTINCT -- Average -- Filtering with HAVING -- CASE Statements Inside Aggregate Functions -- Exercises Using the Included Database -- Chapter 7 Window Functions and Subqueries -- ROW NUMBER -- RANK and DENSE RANK -- NTILE -- Aggregate Window Functions -- LAG and LEAD -- Exercises Using the Included Database -- Chapter 8 Date and Time Functions -- Setting datetime Field Values -- EXTRACT and DATE_PART -- DATE_ADD and DATE_SUB -- DATEDIFF -- TIMESTAMPDIFF -- Date Functions in Aggregate Summaries and Window Functions -- Exercises -- Chapter 9 Exploratory Data Analysis with SQL -- Demonstrating Exploratory Data Analysis with SQL -- Exploring the Products Table -- Exploring Possible Column Values -- Exploring Changes Over Time -- Exploring Multiple Tables Simultaneously -- Exploring Inventory vs. Sales -- Exercises -- Chapter 10 Building SQL Datasets for Analytical Reporting -- Thinking Through Analytical Dataset Requirements -- Using Custom Analytical Datasets in SQL: CTEs and Views -- Taking SQL Reporting Further -- Exercises -- Chapter 11 More Advanced Query Structures -- UNIONs -- Self-Join to Determine To-Date Maximum -- Counting New vs. Returning Customers by Week -- Summary -- Exercises -- Chapter 12 Creating Machine Learning Datasets Using SQL -- Datasets for Time Series Models -- Datasets for Binary Classification -- Creating the Dataset -- Expanding the Feature Set -- Feature Engineering -- Taking Things to the Next Level -- Exercises -- Chapter 13 Analytical Dataset Development Examples -- What Factors Correlate with Fresh Produce Sales? -- How Do Sales Vary by Customer Zip Code, Market Distance, and Demographic Data? -- How Does Product Price Distribution Affect Market Sales? -- Chapter 14 Storing and Modifying Data -- Storing SQL Datasets as Tables and Views -- Adding a Timestamp Column -- Inserting Rows and Updating Values in Database Tables -- Using SQL Inside Scripts -- In Closing -- Exercises -- Appendix Answers to Exercises -- Chapter 1: Data Sources -- Answers -- Chapter 2: The SELECT Statement -- Answers -- Chapter 3: The WHERE Clause -- Answers -- Chapter 4: CASE Statements -- Answers -- Chapter 5: SQL JOINs -- Answers -- Chapter 6: Aggregating Results for Analysis -- Answers -- Chapter 7: Window Functions and Subqueries -- Answers -- Chapter 8: Date and Time Functions -- Answers -- Chapter 9: Exploratory Data Analysis with SQL -- Answers -- Chapter 10: Building SQL Datasets for Analytical Reporting -- Answers -- Chapter 11: More Advanced Query Structures -- Answers -- Chapter 12: Creating Machine Learning Datasets Using SQL -- Answers -- Chapter 14: Storing and Modifying Data |
| Record Nr. | UNINA-9910555033103321 |
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Teate Renee M.
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| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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SQL for data scientists : a beginner's guide for building datasets for analysis / / Renee M. Teate
| SQL for data scientists : a beginner's guide for building datasets for analysis / / Renee M. Teate |
| Autore | Teate Renee M. |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2021] |
| Descrizione fisica | 1 online resource (291 pages) |
| Disciplina | 005.756 |
| Soggetto topico |
SQL (Computer program language)
software data science information analysis text and data mining programming language |
| ISBN |
1-119-66939-1
1-119-66938-3 1-119-66937-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cover -- Title Page -- Copyright Page -- About the Author -- About the Technical Editor -- Acknowledgments -- Contents at a Glance -- Contents -- Introduction -- Who I Am and Why I'm Writing About This Topic -- Who This Book Is For -- Why You Should Learn SQL if You Want to Be a Data Scientist -- What I Hope You Gain from This Book -- Conventions -- Reader Support for This Book -- Companion Download Files -- How to Contact the Publisher -- How to Contact the Author -- Chapter 1 Data Sources -- Data Sources -- Tools for Connecting to Data Sources and Editing SQL -- Relational Databases -- Dimensional Data Warehouses -- Asking Questions About the Data Source -- Introduction to the Farmer's Market Database -- A Note on Machine Learning Dataset Terminology -- Exercises -- Chapter 2 The SELECT Statement -- The SELECT Statement -- The Fundamental Syntax Structure of a SELECT Query -- Selecting Columns and Limiting the Number of Rows Returned -- The ORDER BY Clause: Sorting Results -- Introduction to Simple Inline Calculations -- More Inline Calculation Examples: Rounding -- More Inline Calculation Examples: Concatenating Strings -- Evaluating Query Output -- SELECT Statement Summary -- Exercises Using the Included Database -- Chapter 3 The WHERE Clause -- The WHERE Clause -- Filtering SELECT Statement Results -- Filtering on Multiple Conditions -- Multi-Column Conditional Filtering -- More Ways to Filter -- BETWEEN -- IN -- LIKE -- IS NULL -- A Warning About Null Comparisons -- Filtering Using Subqueries -- Exercises Using the Included Database -- Chapter 4 CASE Statements -- CASE Statement Syntax -- Creating Binary Flags Using CASE -- Grouping or Binning Continuous Values Using CASE -- Categorical Encoding Using CASE -- CASE Statement Summary -- Exercises Using the Included Database -- Chapter 5 SQL JOINs -- Database Relationships and SQL JOINs -- A Common Pitfall when Filtering Joined Data -- JOINs with More than Two Tables -- Exercises Using the Included Database -- Chapter 6 Aggregating Results for Analysis -- GROUP BY Syntax -- Displaying Group Summaries -- Performing Calculations Inside Aggregate Functions -- MIN and MAX -- COUNT and COUNT DISTINCT -- Average -- Filtering with HAVING -- CASE Statements Inside Aggregate Functions -- Exercises Using the Included Database -- Chapter 7 Window Functions and Subqueries -- ROW NUMBER -- RANK and DENSE RANK -- NTILE -- Aggregate Window Functions -- LAG and LEAD -- Exercises Using the Included Database -- Chapter 8 Date and Time Functions -- Setting datetime Field Values -- EXTRACT and DATE_PART -- DATE_ADD and DATE_SUB -- DATEDIFF -- TIMESTAMPDIFF -- Date Functions in Aggregate Summaries and Window Functions -- Exercises -- Chapter 9 Exploratory Data Analysis with SQL -- Demonstrating Exploratory Data Analysis with SQL -- Exploring the Products Table -- Exploring Possible Column Values -- Exploring Changes Over Time -- Exploring Multiple Tables Simultaneously -- Exploring Inventory vs. Sales -- Exercises -- Chapter 10 Building SQL Datasets for Analytical Reporting -- Thinking Through Analytical Dataset Requirements -- Using Custom Analytical Datasets in SQL: CTEs and Views -- Taking SQL Reporting Further -- Exercises -- Chapter 11 More Advanced Query Structures -- UNIONs -- Self-Join to Determine To-Date Maximum -- Counting New vs. Returning Customers by Week -- Summary -- Exercises -- Chapter 12 Creating Machine Learning Datasets Using SQL -- Datasets for Time Series Models -- Datasets for Binary Classification -- Creating the Dataset -- Expanding the Feature Set -- Feature Engineering -- Taking Things to the Next Level -- Exercises -- Chapter 13 Analytical Dataset Development Examples -- What Factors Correlate with Fresh Produce Sales? -- How Do Sales Vary by Customer Zip Code, Market Distance, and Demographic Data? -- How Does Product Price Distribution Affect Market Sales? -- Chapter 14 Storing and Modifying Data -- Storing SQL Datasets as Tables and Views -- Adding a Timestamp Column -- Inserting Rows and Updating Values in Database Tables -- Using SQL Inside Scripts -- In Closing -- Exercises -- Appendix Answers to Exercises -- Chapter 1: Data Sources -- Answers -- Chapter 2: The SELECT Statement -- Answers -- Chapter 3: The WHERE Clause -- Answers -- Chapter 4: CASE Statements -- Answers -- Chapter 5: SQL JOINs -- Answers -- Chapter 6: Aggregating Results for Analysis -- Answers -- Chapter 7: Window Functions and Subqueries -- Answers -- Chapter 8: Date and Time Functions -- Answers -- Chapter 9: Exploratory Data Analysis with SQL -- Answers -- Chapter 10: Building SQL Datasets for Analytical Reporting -- Answers -- Chapter 11: More Advanced Query Structures -- Answers -- Chapter 12: Creating Machine Learning Datasets Using SQL -- Answers -- Chapter 14: Storing and Modifying Data |
| Record Nr. | UNINA-9910676542403321 |
|
Teate Renee M.
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| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Strategic Analytics [[electronic resource] ] : Advancing Strategy Execution and Organizational Effectiveness
| Strategic Analytics [[electronic resource] ] : Advancing Strategy Execution and Organizational Effectiveness |
| Autore | Levenson Alec |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Oakland, : Berrett-Koehler Publishers, 2015 |
| Descrizione fisica | 1 online resource (179 p.) |
| Disciplina | 658.4/012 |
| Soggetto topico |
Strategic planning - Statistical methods
Management Decision making Organizational effectiveness Personnel management Business & Economics Management Theory personnel administration management planning statistical method information analysis |
| ISBN | 1-62656-057-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910797787203321 |
|
Levenson Alec
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| Oakland, : Berrett-Koehler Publishers, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Strategic Analytics : Advancing Strategy Execution and Organizational Effectiveness
| Strategic Analytics : Advancing Strategy Execution and Organizational Effectiveness |
| Autore | Levenson Alec |
| Edizione | [First edition] |
| Pubbl/distr/stampa | Oakland : , : Berrett-Koehler Publishers, , 2015 |
| Descrizione fisica | 1 online resource (179 pages) |
| Disciplina | 658.4/012 |
| Soggetto topico |
Strategic planning - Statistical methods
Management Decision making Organizational effectiveness Personnel management Business & Economics Management Theory personnel administration management planning statistical method information analysis |
| ISBN |
9781626560574
1626560579 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cover Page -- Title Page -- Copyright Page -- Dedication -- Contents -- List of Figures and Tables -- Preface -- Introduction Integrating Enterprise and Human Capital Analytics -- Part I Why Do Strategic Analytics? -- Chapter 1 Of Elephants and Incomplete Analytics -- Chapter 2 Beware the ROI Bogeyman and Other Monsters under the Bed -- Part II How to Do Strategic Analytics -- Chapter 3 Put the Horse in Front of the Cart-Where to Focus the Analysis -- Chapter 4 Step 1-Competitive Advantage Analytics -- Chapter 5 Step 2-Enterprise Analytics -- Chapter 6 Step 3-Human Capital Analytics -- Chapter 7 Putting It All Together -- Chapter 8 Application-Customer Retention and Profitable Growth -- Chapter 9 Application-Go-to-Market Strategies and Effectiveness -- Part III Diving Deeper: How to Make Current Practice Better -- Chapter 10 Critical Roles, Competencies, and Performance -- Chapter 11 Making Sense of Sensing Data -- Chapter 12 Evaluating Human Capital Development: Build versus Buy versus Redesign -- Conclusion Key Learning and Action Points -- References -- Appendix Strategic Analytics Diagnostic Interview Template -- Acknowledgments -- Index -- About the Author -- Footnotes -- Chapter 3 -- Chapter 6. |
| Record Nr. | UNINA-9910972397503321 |
|
Levenson Alec
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| Oakland : , : Berrett-Koehler Publishers, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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