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Statistical Data Analysis using R and STATA Training Workshop

This course will provide an overview of data analytics using STATA and R statistical software. The course will equip you with a comprehensive introduction to STATA and R and its various uses in data management and analysis. You will learn in detail and gain practical experience in manipulating, exploring, visualizing, and modelling different types of data using STATA and R. By the end of the course, you will be able to interpret the statistical outputs/results and the application in real-life situations. Through R you will learn and apply the basics of programming and its application in data visualization and modelling. Requirement: 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.

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Online via Live Zoom Classes

2 Weeks

11th - 22nd Mar 2024
6th - 17th May 2024
26th Aug - 6th Sept 2024
4th - 15th Nov 2024

HG Training Center, Nairobi, Kenya

5 Days

6th - 10th May 2024

Course Objectives
  1. Manage data, including data manipulation and cleaning using STATA

  1. Perform descriptive analysis and Perform Relation Analysis

  1. Conduct modeling using STATA

  1. Learn the basics of R

  1. Learn data manipulation and organization using R

  1. Perform relation analysis and interpretation of the results using R

  2. Perform statistical modelling and interpretation of the results using R

Training Programme

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

Certification
Participants will be issued Digital Certification after successful completion of the training.
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