ABOUT THE COURSE
This course will provide a set of foundational statistical modeling tools for data Analysis using STATA & Ms. Excel, students will be introduced to methods, theory, and applications of correlation and linear statistical models, covering the topics of simple linear regression, Multiple linear regression, logistic regression, goodness of fit, and various strategies for variable selection and model comparison. Along the way, you’ll be introduced interpreting data and performing calculations on real data from published studies.
WHAT YOU WILL LEARN
• interpret the coefficient of correlation, the coefficient of determination
• Conduct a test of hypothesis to determine whether the coefficient of correlation in the population is zero.
• Practical use of Correlation and Regression with a practical example
• studying the relationship between two or more variables such as the impact of export and import on Gross Domestic Product ( GDP) & so on.
• interpret the multiple standard error of estimate, the coefficient of multiple determination, and the adjusted coefficient of multiple determination
• Interpretation of results from Regression analysis including R-Square, Significance F and p-values, Coefficients, Residuals and Best Fit Model
• Detailed Illustration of Binary Logistic Regression Analysis with Practical Example
• Conduct a test of hypothesis to determine whether regression coefficients differ from zero.
• Conduct a test of hypothesis on each of the regression coefficients.
• Evaluate the performance of the regression model and make predictions based on the selected model
WHO THIS COURSE IS FOR?
✓ Students and researchers looking to master STATA & Ms. Excel skills and publish in high impact journals
✓ Professionals looking for a career in analytics in corporate sector
✓ Faculty members and teachers looking to master STATA & Ms. Excel and advance their data analysis skills
✓ Research institutions and NGOs
✓ Entrepreneurs
✓ Suppliers
✓ Technical People
✓ Anyone involved in Data Management and Data Analysis
COURSE OUTLINE
Model 1: Measures of Associan
Unit 1:Pearson’s correlation
Unit 2: Spearman Rank Correlation
Unit 3: Chi-square
Model 2: Statistical model fitting
Unit 1:Simple Linear regression
Unit 2: Multiple Linear Regression
Unit 3: Logistic Regression
DURATION
This is 6 days training program at evening (4 pm – 7pm) and the schedule will be as follows
| Start date: 08/08/ 2023 | End date: 15/08/ 2023 | ||
| Week/ Day | Tuesday | Wednesday | Thursday |
| Week One | 08/08/2023 | 09/08/2023 | 10/08/2023 |
| Week Two | 15/08/2023 | 16/08/2023 | 17/08/2023 |
COST
The course fee is $50 per person (course materials, refreshment & certificate).
NOTE: All participants are encouraged to bring their own laptop.