Learn Data Analytics with Stata | Franz Buscha | Skillshare

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Learn Data Analytics with Stata

teacher avatar Franz Buscha

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Taught by industry leaders & working professionals
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Watch this class and thousands more

Get unlimited access to every class
Taught by industry leaders & working professionals
Topics include illustration, design, photography, and more

Lessons in This Class

83 Lessons (10h 47m)
    • 1. Starting 1 - Stata's Interface

      7:40
    • 2. Starting 2 - Using Help

      5:23
    • 3. Starting 3 - Stata's Command Syntax

      4:10
    • 4. Starting 4 - .do and .ado Files

      7:37
    • 5. Starting 5 - Creating and Viewing Logs

      5:11
    • 6. Starting 6 - Loading and Importing Data

      9:11
    • 7. Exploring Data 1 - Viewing/Editing Raw Data

      4:21
    • 8. Exploring Data 2 - Describing and Summarizing Data

      7:33
    • 9. Exploring Data 3 - Tabulating and Tables

      8:42
    • 10. Exploring Data 4 - Missing Data

      7:41
    • 11. Exploring Data 5 - Numeric Distribution Analysis

      6:00
    • 12. Exploring Data 6 - Using Weights

      5:09
    • 13. Manipulating 1 - Recoding a Variable

      4:53
    • 14. Manipulating 2 - Creating and Replacing Variables

      6:39
    • 15. Manipulating 3 - Naming and Labelling Variables

      7:31
    • 16. Manipulating 4 - Advanced Variable Creation

      4:58
    • 17. Manipulating 5 - Creating Indicator Variables

      6:58
    • 18. Manipulating 6 - Dropping and Keeping Data

      2:58
    • 19. Manipulating 7 - Saving Data

      4:05
    • 20. Manipulating 8 - Converting String Data

      7:15
    • 21. Manipulating 9 - Combining Datasets

      6:35
    • 22. Manipulating 10 - Macro's and Loop's

      9:33
    • 23. Manipulating 11 - Accessing Stored Information

      6:41
    • 24. Manipulating 12 - Multiple Loops

      4:26
    • 25. Manipulating 13 - Date Variables

      8:24
    • 26. Manipulating 14 - Subscripting over Groups

      11:03
    • 27. Visual 1 - Introduction to Graph command

      6:29
    • 28. Visual 2 - Bar Graphs and Dot Charts

      7:48
    • 29. Visual 3 - Distribution Plots

      9:13
    • 30. Visual 4 - Pie Charts

      6:20
    • 31. Visual 5 - Scatterplot and Lines of Best Fit

      9:22
    • 32. Visual 6 - Drawing Custom Functions

      5:28
    • 33. Visual 7 - Contour Plots

      9:04
    • 34. Visual 8 - Jitter in Scatterplots

      5:55
    • 35. Visual 9 - Combining Graphs

      7:34
    • 36. Visual 10 - Sunflower Plots

      7:45
    • 37. Visual 11 - Sizing Graphs

      4:37
    • 38. Visual 12 - Graphing by Groups

      6:27
    • 39. Visual 13 - Changing Colours

      7:24
    • 40. Basic tests 1 - Association Between Two Categorical Variables

      6:07
    • 41. Basic tests 2 - Testing Means

      6:38
    • 42. Basic tests 3 - Pearson's and Tetrachoric Correlation

      6:46
    • 43. Basic tests 4 - Analysis of Variance (ANOVA)

      6:14
    • 44. Linear Regression 1 - Basic Ordinary Least Squares

      6:39
    • 45. Linear Regression 2 - Factor Explanatory Variables in OLS

      7:30
    • 46. Linear Regression 3 - Diagnostics

      16:14
    • 47. Linear Regression 4 - Log Dependent Variable and Interactions

      8:20
    • 48. Linear Regression 5 - Hypothesis Testing

      5:16
    • 49. Linear Regression 6 - Presenting Regression Results in Tables

      7:55
    • 50. Linear Regression 7 - Standardized Estimates

      5:24
    • 51. Linear regression 8 - Graphing Estimates

      10:20
    • 52. Linear regression 9 - Oaxaca Decomposition

      15:53
    • 53. Linear regression 10 - Mixed Models

      18:57
    • 54. Choice Models 1 - Logit and Probit Regression

      7:27
    • 55. Choice Models 2 - Logit and Probit Goodness-of-Fit and Marginal Effects

      10:33
    • 56. Choice Models 3 - Ordered and Multinomial Logit Regression

      12:52
    • 57. Choice models 4 -Fractional Dependent Variable Models

      14:35
    • 58. Simulation 1 - Drawing pseudorandom numbers

      6:43
    • 59. Simulation 2 - Data Generating Process

      6:17
    • 60. Simulation 3 - Violating Estimator Assumptions

      5:52
    • 61. Simulation 4 - Monte Carlo Simulation

      5:22
    • 62. Matrix 1 - Matrix Operations

      10:59
    • 63. Matrix 2 - Matrix Functions

      6:05
    • 64. Matrix 3 - Matrix Subscripting

      6:04
    • 65. Matrix 4 - Matrix Operations with Data

      8:39
    • 66. Power 1 - Sample Size

      14:55
    • 67. Power 2 - Power and Effect Size

      8:05
    • 68. Power 3 - Simple Regression

      8:09
    • 69. Instrument 1 - Instrumental Variable Regression

      20:21
    • 70. Instrument 2 - Multiple Endogenous Variables

      12:17
    • 71. Instrument 3 - Non-linear Instrumental Variable Regression

      14:39
    • 72. Instrument 4 - Heckman Selection Models

      11:32
    • 73. Panel 1 - Setting up Panel Data

      8:55
    • 74. Panel 2 - Panel Data Descriptives

      9:03
    • 75. Panel 3 - Lags and Leads

      10:47
    • 76. Panel 4 - Linear Panel Estimators

      12:33
    • 77. Panel 5 - The Hausman Test

      5:26
    • 78. Panel 6 - Non-Linear Panel Estimators

      8:52
    • 79. Count 1 - Features of Count Data

      7:46
    • 80. Count 2 - Poisson Regression

      9:28
    • 81. Count 3 - Negative Binomial Regression

      7:59
    • 82. Count 4 - Truncated and Censored Count Regression

      8:02
    • 83. Count 5 - Hurdle Count Regression

      8:44
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About This Class

An extensive introduction to Data Analytics with Stata

Learning and applying new statistical techniques can be daunting experience.

This is especially true once one engages with “real life” data sets that do not allow for easy “click-and-go” analysis, but require a deeper level of understanding of programme coding, data manipulation, output interpretation, output formatting and selecting the right kind of analytical methodology.

In this class you will receive a comprehensive introduction to Stata and its various uses in modern data analysis. You will learn to understand the various options that Stata gives you in manipulating, exploring, visualizing and modelling complex types of data. By the end of the class you will feel confident in your ability to engage with Stata and handle complex data analytics. The focus of this class will consistently be on creating a “good practice” and emphasising the practical application – and interpretation – of commonly used statistical techniques without resorting to deep statistical theory or equations.  

This class will focus on providing an overview of data analysis with Stata.

No prior engagement with is Stata needed.

Some basic quantitative/statistical knowledge will be required; this is not an introduction to statistics course but rather the application and interpretation of such using Stata.   

Topics covered will include:

  1. Getting started with Stata
  2. Viewing and exploring data
  3. Manipulating data
  4. Visualising data
  5. Correlation and ANOVA
  6. Regression including diagnostics (Ordinary Least Squares)
  7. Regression model building
  8. Hypothesis testing
  9. Binary outcome models (Logit and Probit)
  10. Categorical choice models (Ordered Logit and Multinomial Logit)
  11. Simulation techniques

Meet Your Teacher

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Franz Buscha

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