The Complete Guide to Stata

The Complete Guide to Stata, available at $94.99, has an average rating of 4.43, with 304 lectures, based on 233 reviews, and has 1289 subscribers.

You will learn about An essential introduction to Stata Data manipulation in Stata Data analysis in Stata Regression modelling Stata code Advanced Stata code Fast, and to the point, useful tips to use in Stata Data management Programming Graphics Statistics Basic plot types Intermediate plot types Advanced plot types This course is ideal for individuals who are Anyone wanting to work with Stata or Data analysts or Data scientists or Quantitative degree students or Quantitative business users or Economists, Social Scientists, Political Scientists, Biostatisticians, and other disciplines or Those wanting to skill-up in Stata It is particularly useful for Anyone wanting to work with Stata or Data analysts or Data scientists or Quantitative degree students or Quantitative business users or Economists, Social Scientists, Political Scientists, Biostatisticians, and other disciplines or Those wanting to skill-up in Stata.

Enroll now: The Complete Guide to Stata

Summary

Title: The Complete Guide to Stata

Price: $94.99

Average Rating: 4.43

Number of Lectures: 304

Number of Published Lectures: 304

Number of Curriculum Items: 304

Number of Published Curriculum Objects: 304

Original Price: £89.99

Quality Status: approved

Status: Live

What You Will Learn

An essential introduction to Stata
Data manipulation in Stata
Data analysis in Stata
Regression modelling
Stata code
Advanced Stata code
Fast, and to the point, useful tips to use in Stata
Data management
Programming
Graphics
Statistics
Basic plot types
Intermediate plot types
Advanced plot types

Who Should Attend

Anyone wanting to work with Stata
Data analysts
Data scientists
Quantitative degree students
Quantitative business users
Economists, Social Scientists, Political Scientists, Biostatisticians, and other disciplines
Those wanting to skill-up in Stata

Target Audiences

Anyone wanting to work with Stata
Data analysts
Data scientists
Quantitative degree students
Quantitative business users
Economists, Social Scientists, Political Scientists, Biostatisticians, and other disciplines
Those wanting to skill-up in Stata

Make sure to check out my twitter feed for monthly promo codes and other updates (@easystats3)

The Complete Guide to 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 course you will receive a comprehensive introduction to Stata and its various uses in modern data analysis. You will learn to understand the many options that Stata gives you in manipulating, exploring, visualizing and modelling complex types of data. By the end of the course you will feel confident in your ability to engage with Stata and handle complex data analytics. The focus of each session 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 course consists of three sub-courses that will 1) teach you the essentials of Stata 2) provide you with tips and tricks for Stata and 3) teach you advanced data visualization techniques.

No prior engagement with is Stata needed. Some prior statistics knowledge will help but is not necessary.

The course is aimed at anyone interested in data analytics using Stata.

Like for other professional statistical packages the course focuses on the proper application – and interpretation – of code.

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 include:

Getting started with Stata
Viewing and exploring data
Manipulating data
Visualising data
Correlation and ANOVA
Regression including diagnostics (Ordinary Least Squares)
Regression model building
Hypothesis testing
Binary outcome models (Logit and Probit)
Fractional response models (Fractional Logit and Beta Regression)
Categorical choice models (Ordered Logit and Multinomial Logit)
Simulation techniques (Random Numbers and Simulation)
Count data models (Poisson and Negative Binomial Regression)
Survival data analysis (Parametric, Cox-Proportional Hazard and Parametric Survival Regression)
Panel data analysis (Long Form Data, Lags and Leads, Random and Fixed Effects, Hausman Test and Non-Linear Panel Regression)
Difference-in-differences analysis (Difference-in-Difference and Parallel Trends)
Instrumental variable regression (Endogenous Variables, Sample Selection, Non-Linear Endogenous Models)
Epidemiological tables (Cohort Studies, Case-Control Studies and Matched Case-Control Studies)
Power analysis (Sample Size, Power Size and Effect Size)
Matrix operations (Matrix operators, Matrix functions, Matrix subscripting)

There are also 125 tips and tricks for Stata. These tips are aimed at helping you become a Stata master! They cover a wide range of issues the following topics:

Data management
Graphing
Statistics
Programming.

Each tip is designed to be stand-alone and will take no more than 2 minutes.

Finally, you will be shown some of the most important data visualization methods and learn what ae the advantages and disadvantages of each technique are. A wide variety of graphs are highlighted in great detail including:

Histograms
Density plots
Spike plots
Rootograms
Box plots
Violin plots
Stem-and-Leaf plots
Quantile plots
Bar graphs
Pie charts
Dot charts
Radar plots
Scatter plots
Heat plots
Hex plots
Sunflower plots
Lines of best fit
Area plots
Line plots
Range plots
Rainbow plots
Jitter plots
Table plots
Baloon plots
Mosaic plots
Chernoff faces
Sparkling plots
Bubble plots
and more

Depending on your desired learning outcomes you may wish to focus on specific parts.

To gain a basic understanding of Stata watch sections 2, 3, 4, 5, 6, 7 and 8
To learn advanced Stata concepts watch sections 8, 9, 10, 11, 12, 13, 14, 15, 16 and 17
To learn fast tips for Stata watch sections 18, 19, 20 and 21
To learn all about data visualisation in Stata watch sections 5, 21, 22, 23, 24, 25 and 26
To learn data management concepts watch sections 3, 4 and 18

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Essential Stata – Getting Started

Lecture 1: The Stata Interface

Lecture 2: Using Help in Stata

Lecture 3: Command Syntax

Lecture 4: .do and .ado Files

Lecture 5: Log Files

Lecture 6: Importing Data

Chapter 3: Essential Stata – Exploring Data

Lecture 1: Viewing Raw Data

Lecture 2: Describing and Summarizing

Lecture 3: Tabulating and Tables

Lecture 4: Missing Values

Lecture 5: Numerical Distributional Analysis

Lecture 6: Using Weights

Lecture 7: The New Table Command (Stata 17)

Chapter 4: Essential Stata – Manipulating Data

Lecture 1: Recoding an Existing Variable

Lecture 2: Creating New Variables, Replacing Old Variables

Lecture 3: Naming and Labelling Variables

Lecture 4: Extensions to Generate

Lecture 5: Indicator Variables

Lecture 6: Keep and Drop Data/Variables

Lecture 7: Saving Data

Lecture 8: Converting String Data

Lecture 9: Combining Data

Lecture 10: Using Macro's and Loop's Effectively

Lecture 11: Accessing Stored Information

Lecture 12: Multiple Loops

Lecture 13: Date Variables

Lecture 14: Subscripting over Groups

Chapter 5: Essential Stata – Visualizing Data

Lecture 1: Graphing in Stata

Lecture 2: Bar Graphs and Dot Charts

Lecture 3: Graphing Distributions

Lecture 4: Pie Charts

Lecture 5: Scatterplots and Lines of Best Fit

Lecture 6: Graphing Custom Functions

Lecture 7: Contour Plots (and Interaction Effects)

Lecture 8: Jitter Data in Scatterplots

Lecture 9: Sunflower Plots

Lecture 10: Combining Graphs

Lecture 11: Changing Graph Sizes

Lecture 12: Graphing by Groups

Lecture 13: Changing Graph Colours

Lecture 14: Adding Text to Graphs

Lecture 15: Scatterplots with Categories

Chapter 6: Essential Stata – Testing Means, Correlations and ANOVA

Lecture 1: Association Between Two Categorical Variables

Lecture 2: Testing Means

Lecture 3: Bivariate Correlation

Lecture 4: Analysis of Variance (ANOVA)

Chapter 7: Essential Stata – Linear Regression

Lecture 1: Ordinary Least Squares (OLS) Regression

Lecture 2: Factor Variables in OLS Regression

Lecture 3: Diagnostic Statistics for OLS Regression

Lecture 4: Log Dependent Variables and Interaction Effects in OLS Regression

Lecture 5: Hypothesis Testing in OLS Regression

Lecture 6: Presenting Estimates from OLS Regression

Lecture 7: Standardizing Regression Estimates

Lecture 8: Graphing Regression Estimates

Lecture 9: Oaxaca Decomposition Analysis

Lecture 10: Mixed Models: Random Intercepts and Random Coefficients

Lecture 11: Constrained Linear Regression

Chapter 8: Essential Stata – Categorical Choice Models

Lecture 1: Binary Choice Models (Logit/Probit Regression)

Lecture 2: Diagnostics and Interpretation of Logit and Probit Regression

Lecture 3: Ordered and Multinomial Choice Models

Lecture 4: Fractional Logit, Beta Regression and Zero-inflated Beta Regression

Chapter 9: Essential Stata – Random Numbers and Simulation

Lecture 1: Random Numbers

Lecture 2: Data Generating Process

Lecture 3: Simulating a Violation of Statistical Assumptions

Lecture 4: Monte Carlo Simulation

Chapter 10: Essential Stata – Count Data Models

Lecture 1: Features of Count Data

Lecture 2: Poisson Regression

Lecture 3: Negative Binomial Regression

Lecture 4: Truncated and Censored Count Regression

Lecture 5: Hurdle Count Regression

Chapter 11: Essential Stata – Survival Analysis

Lecture 1: What is Survival Analysis?

Lecture 2: Setting up Survival Data

Lecture 3: Descriptive Statistics in Survival Data

Lecture 4: Non-parametric Survival Analysis

Lecture 5: Cox Proportional Hazard's Model

Lecture 6: Diagnostics for Cox Models

Lecture 7: Parametric Survival Analysis

Chapter 12: Essential Stata – Panel Data Analysis

Lecture 1: Setting up Panel Data

Lecture 2: Panel Data Descriptives

Lecture 3: Lags and Leads

Lecture 4: Linear Panel Estimators

Lecture 5: The Hausman Test

Lecture 6: Non-Linear Panel Estimators

Chapter 13: Essential Stata – Difference-in-Differences Analysis

Lecture 1: Difference-in-Differences Estimation

Lecture 2: Parallel Trend Assumption

Lecture 3: Difference-in-Differences without Parallel Trends

Instructors

F. Buscha
Professor

Rating Distribution

1 stars: 7 votes
2 stars: 1 votes
3 stars: 26 votes
4 stars: 59 votes
5 stars: 140 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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