Chapter 1: Introduction to STATA
- Lesson 1: What is STATA?
- Lesson 2: History and Importance of STATA
- Lesson 3: Installing STATA (Windows, macOS, Linux)
- Lesson 4: STATA Interface and Navigation
- Lesson 5: STATA vs Other Statistical Software
Chapter 2: Getting Started with STATA
- Lesson 1: Understanding STATA File Types (.dta, .do, .log)
- Lesson 2: Opening, Saving, and Exporting Data
- Lesson 3: Creating and Managing STATA Do-Files
- Lesson 4: STATA Command Syntax and Execution
- Lesson 5: Using Help and Documentation in STATA
Chapter 3: Data Management in STATA
- Lesson 1: Importing Data (CSV, Excel, SPSS, SAS)
- Lesson 2: Creating and Modifying Variables
- Lesson 3: Sorting, Filtering, and Searching Data
- Lesson 4: Merging and Appending Datasets
- Lesson 5: Handling Missing Values in STATA
Chapter 4: Data Cleaning and Transformation
- Lesson 1: Recoding Variables
- Lesson 2: Labeling Variables and Values
- Lesson 3: Generating New Variables
- Lesson 4: Reshaping Data (Wide to Long and Vice Versa)
- Lesson 5: Detecting and Handling Outliers
Chapter 5: Descriptive Statistics and Data Summarization
- Lesson 1: Summary Statistics (mean, median, variance)
- Lesson 2: Frequency Tables and Cross-tabulations
- Lesson 3: Measures of Dispersion (standard deviation, IQR)
- Lesson 4: Histograms, Boxplots, and Kernel Density Plots
- Lesson 5: Customizing Summary Statistics Output
Chapter 6: Basic Data Visualization in STATA
- Lesson 1: Scatter Plots and Line Graphs
- Lesson 2: Bar Charts and Pie Charts
- Lesson 3: Box Plots and Histograms
- Lesson 4: Customizing Graphs in STATA
- Lesson 5: Exporting and Saving Graphs
Chapter 7: Introduction to STATA Programming
- Lesson 1: Writing and Running Do-Files
- Lesson 2: Using Macros in STATA
- Lesson 3: Using Loops and Conditional Statements
- Lesson 4: Creating Basic STATA Programs
- Lesson 5: Debugging STATA Scripts
Chapter 8: Introduction to Regression Analysis
- Lesson 1: Understanding Linear Regression
- Lesson 2: Running a Simple Linear Regression in STATA
- Lesson 3: Interpreting Regression Output
- Lesson 4: Checking Model Assumptions
- Lesson 5: Reporting Regression Results
Chapter 9: Hypothesis Testing in STATA
- Lesson 1: Introduction to Hypothesis Testing
- Lesson 2: t-tests and ANOVA
- Lesson 3: Chi-Square Tests
- Lesson 4: Correlation and Covariance
- Lesson 5: Statistical Significance and p-values
Chapter 10: Working with Panel Data
- Lesson 1: Introduction to Panel Data
- Lesson 2: Setting Up Panel Data in STATA
- Lesson 3: Descriptive Statistics for Panel Data
- Lesson 4: Fixed Effects vs Random Effects Models
- Lesson 5: Running Basic Panel Data Regressions
Chapter 1: Advanced Data Management in STATA
- Lesson 1: Advanced Merging and Matching Techniques
- Lesson 2: Working with Large Datasets Efficiently
- Lesson 3: Data Imputation Methods
- Lesson 4: Using STATA Frames for Multiple Datasets
- Lesson 5: Automating Data Cleaning with Scripts
Chapter 2: Advanced Regression Techniques
- Lesson 1: Multiple Linear Regression in STATA
- Lesson 2: Logistic Regression and Probit Models
- Lesson 3: Interaction Terms in Regression
- Lesson 4: Robust and Clustered Standard Errors
- Lesson 5: Model Selection and Fit Diagnostics
Chapter 3: Time Series Analysis in STATA
- Lesson 1: Introduction to Time Series Data
- Lesson 2: Stationarity and Differencing
- Lesson 3: Autoregressive and Moving Average Models
- Lesson 4: ARIMA and VAR Models
- Lesson 5: Forecasting with STATA
Chapter 4: Advanced Panel Data Analysis
- Lesson 1: Advanced Fixed and Random Effects Models
- Lesson 2: Generalized Least Squares (GLS) Estimation
- Lesson 3: Dynamic Panel Data Models (GMM)
- Lesson 4: Difference-in-Differences (DiD) Estimation
- Lesson 5: Advanced Panel Data Visualization
Chapter 5: Structural Equation Modeling (SEM)
- Lesson 1: Introduction to SEM
- Lesson 2: Path Analysis and Mediation Models
- Lesson 3: Confirmatory Factor Analysis (CFA)
- Lesson 4: Full Structural Equation Models
- Lesson 5: Reporting SEM Results in STATA
Chapter 6: Advanced Survival Analysis
- Lesson 1: Introduction to Survival Analysis
- Lesson 2: Kaplan-Meier Estimation
- Lesson 3: Cox Proportional Hazards Model
- Lesson 4: Parametric Survival Models
- Lesson 5: Comparing Survival Curves
Chapter 7: Bayesian Analysis in STATA
- Lesson 1: Introduction to Bayesian Methods
- Lesson 2: Bayesian Regression in STATA
- Lesson 3: Markov Chain Monte Carlo (MCMC) Methods
- Lesson 4: Posterior Distributions and Credible Intervals
- Lesson 5: Bayesian Model Comparison
Chapter 8: Machine Learning in STATA
- Lesson 1: Introduction to Machine Learning in STATA
- Lesson 2: Decision Trees and Random Forests
- Lesson 3: Support Vector Machines (SVM)
- Lesson 4: Neural Networks in STATA
- Lesson 5: Model Evaluation and Hyperparameter Tuning
Chapter 9: Advanced STATA Programming
- Lesson 1: Writing Custom Programs in STATA
- Lesson 2: Creating Custom STATA Commands
- Lesson 3: Debugging and Optimizing STATA Code
- Lesson 4: Working with STATA’s Mata Programming Language
- Lesson 5: Automating Reports and Analysis with STATA
Chapter 10: STATA for Economic and Social Research
- Lesson 1: Instrumental Variables (IV) Regression
- Lesson 2: Propensity Score Matching (PSM)
- Lesson 3: Regression Discontinuity Designs (RDD)
- Lesson 4: Synthetic Control Methods
- Lesson 5: Econometric Applications in STATA
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