Course Title: Quantitative Data Management and Analysis with STATA

Introduction:

Welcome to the "Quantitative Data Management and Analysis with STATA" course. In today's data-driven world, the ability to efficiently manage and analyze quantitative data is essential for informed decision-making and evidence-based solutions. This course is designed to equip participants with the skills and knowledge required to effectively handle and analyze quantitative data using the popular statistical software STATA. Whether you're a researcher, analyst, or professional from any field, this course will empower you to confidently navigate the realm of data management and analysis.

Course Objectives: Throughout this course, we aim to achieve the following objectives:

1. Foundations of STATA: Familiarize participants with the STATA interface, basic commands, and data importing techniques.
2. Data Cleaning and Preparation: Learn how to clean, validate, and transform raw data into a structured format suitable for analysis.
3. Descriptive Statistics: Explore techniques to summarize and describe data distributions.
4. Hypothesis Testing: Understand the principles of hypothesis testing and its application in various scenarios.
5. Regression Analysis: Master linear and logistic regression models for exploring relationships and making predictions.
6. Data Visualization: Utilize graphical tools to visually represent data patterns and insights.
7. Panel Data Analysis: Learn to handle and analyze longitudinal data using panel data techniques.
8. Survival Analysis: Understand survival analysis methods to analyze time-to-event data.
9. Advanced Regression Techniques: Delve into advanced regression models, such as multilevel and robust regression.
10. Econometric Analysis: Explore econometric methods for analyzing economic relationships within datasets.
11. Time Series Analysis: Grasp time series concepts and techniques for analyzing temporal data.
12. Data Transformation and Reshaping: Learn how to reshape and restructure data for specific analytical needs.
13. Missing Data Handling: Understand strategies for handling missing data and their potential impact on analyses.
14. Survey Data Analysis: Apply STATA to analyze survey data, accounting for complex sampling designs.
15. Advanced Data Visualization: Explore advanced visualization techniques, including interactive graphs and maps.
16. Meta-Analysis: Understand the principles of meta-analysis and its implementation using STATA.
17. Machine Learning with STATA: Introduction to machine learning techniques available in STATA for predictive modeling.
18. Reporting and Exporting Results: Learn how to generate professional reports and export results for presentations.
19. Quality Control and Validation: Implement quality control measures to ensure accuracy and validity of results.
20. Ethical Considerations: Address ethical considerations in quantitative data analysis, including data privacy and integrity.

Organizational Benefits:

Organizations participating in this course will:

• Strengthen their employees' ability to effectively manage and analyze quantitative data using STATA.
• Enhance decision-making processes by deriving actionable insights from complex datasets.
• Improve research capabilities and methodologies, leading to evidence-based strategies.
• Foster a culture of data-driven decision-making and analytical rigor within the organization.

Target Participants:

This course is tailored for professionals and researchers from diverse fields, including:

• Social sciences, economics, and finance.
• Public health, epidemiology, and healthcare research.
• Business analytics, market research, and data analysis.
• Academic institutions, research organizations, and governmental bodies.

Duration:

5 days

Course Outline:

Module 1: Introduction to STATA and Data Management

• Introduction to STATA software and its interface
• Basics of data management: importing, exporting, and saving data

Module 2: Data Cleaning and Validation

• Identifying and handling missing data
• Data validation and outlier detection techniques

Module 3: Descriptive Statistics and Data Summarization

• Calculating measures of central tendency and dispersion
• Generating frequency distributions and summary tables

Module 4: Introduction to Hypothesis Testing

• Understanding null and alternative hypotheses
• Performing t-tests and chi-square tests in STATA

Module 5: Linear Regression Analysis

• Simple and multiple linear regression models
• Assumptions of linear regression and model interpretation

Module 6: Logistic Regression Analysis

• Logistic regression for binary and categorical outcomes
• Odds ratios, model diagnostics, and interpretation

Module 7: Data Visualization Techniques

• Creating histograms, scatter plots, and bar charts
• Customizing graphs for effective data presentation

Module 8: Panel Data Analysis

• Understanding panel data structures
• Fixed-effects and random-effects panel data models

Module 9: Survival Analysis

• Kaplan-Meier survival curves
• Cox proportional hazards regression

Module 10: Advanced Regression Models

• Polynomial regression, interaction terms, and robust regression
• Heteroscedasticity and autocorrelation testing

Module 11: Econometric Analysis

• Instrumental variable regression
• Endogeneity and selection bias considerations

Module 12: Time Series Analysis

• Time series data components and patterns
• ARIMA modeling for forecasting

Module 13: Data Transformation and Reshaping

• Restructuring data using reshape and merge commands
• Creating new variables and transforming data formats

Module 14: Handling Missing Data

• Imputation techniques: mean, median, regression imputation
• Multiple imputation and sensitivity analysis

Module 15: Survey Data Analysis

• Complex survey design considerations
• Weighting and clustering in survey data analysis

Module 16: Advanced Data Visualization Techniques

• Interactive visualizations using STATA's graph commands
• Geographic data visualization with maps and spatial analysis

Module 17: Introduction to Meta-Analysis

• Combining study results using meta-analysis
• Forest plots and heterogeneity assessment

Module 18: Machine Learning Methods in STATA

• Introduction to machine learning algorithms in STATA
• Classification and regression using machine learning techniques

Module 19: Reporting and Exporting Results

• Generating tables, figures, and reports
• Exporting results to various formats for presentations

Module 20: Quality Control and Validation in Data Analysis

• Cross-checking data for accuracy and consistency
• Data validation techniques and best practices

Module 21: Ethical Considerations in Quantitative Data Analysis

• Data privacy, confidentiality, and ethical considerations
• Ensuring data integrity and responsible data use

General Notes

• All our courses can be Tailor-made to participants' needs
• The participant must be conversant in English
• Presentations are well-guided, practical exercises, web-based tutorials, and group work. Our facilitators are experts with more than 10 years of experience.
• Upon completion of training the participant will be issued with a Foscore development center certificate (FDC-K)
• Training will be done at the Foscore development center (FDC-K) centers. We also offer inhouse and online training on the client schedule
• Course duration is flexible and the contents can be modified to fit any number of days.
• The course fee for onsite training includes facilitation training materials, 2 coffee breaks, a buffet lunch, and a Certificate of successful completion of Training. Participants will be responsible for their own travel expenses and arrangements, airport transfers, visa application dinners, health/accident insurance, and other personal expenses.
• Accommodation, pickup, freight booking, and Visa processing arrangement, are done on request, at discounted prices.
• Tablet and Laptops are provided to participants on request as an add-on cost to the training fee.
• One-year free Consultation and Coaching provided after the course.
• Register as a group of more than two and enjoy a discount of (10% to 50%)
• Payment should be done before commence of the training or as agreed by the parties, to the FOSCORE DEVELOPMENT CENTER account, so as to enable us to prepare better for you.
• For any inquiries reach us at training@fdc-k.org or +254712260031
• Website:www.fdc-k.org