Manage data, including data manipulation and cleaning using STATA
Perform descriptive analysis and Perform Relation Analysis
Conduct modeling using STATA
Learn the basics of R
Learn data manipulation and organization using R
Perform relation analysis and interpretation of the results using R
Perform statistical modelling and interpretation of the results using R
Session 1:Introduction to STATA
Key components of STATA and STATA syntax
STATA commands and do-file
Opening and clearing a database
Compressing databases
Changing the working directory
Session 2: Data management
Data description, code-book, inspect and summarize
View, edit and label variables
Merge datasets/compare datasets/Transpose a dataset
Create and replace variables
Rename/Recode and drop variables
Replace/Fill in missing values
Destring and To string variables
Session 3: Descriptive statistics
Descriptive statistics for nominal and ordinal variables
Summary statistics for Interval and Ratio variables
Tabulation and tables
Correlations, covariances and confidence intervals
Graphics and data visualization
Session 4: Analyzing relationships between variables
One and two sample t-tests
Analysis of variance (ANOVA)
Hypothesis testing
Session 5: Regression Analysis
Scatter plots
Correlation analysis
Simple and multiple linear regression analysis
Ordinary Least Squares analysis
Interpretation of the results
Session 6: Modeling in STATA
Probit and Logit models and their variations
Poisson and Binomial models
Linear probability model
Marginal Effects
 Data analysis and modelling using R and R Studio
Session 1: Introduction to R and R studio
Installing R studio and its packages
Key components of R and Core programming principles
Importing data into R
Exploring your dataset using R
Session 2: Descriptive statistics
Central tendencies: mean, median and mode
Variance, standard deviation, quantiles and quartiles
Graphics and Data visualization
Session 3: Relationship/Association Analysis
Correlation analysis
Regression analysis
Simple linear regression analysis
Multiple regression analysis
Ordinary Least Squares (OLS)
Analysis of variance (ANOVA)
Session 4: Probability and Hypothesis testing
One sample t-test
Two sample t-test
Paired samples t-test
Session 5: Statistical modelling
Logit model and its variations
Probit model and its variations
OLS regression model
Marginal effects and their interpretation
