Module 1: Introduction to Stata and M&E Concepts

• Overview of the Stata interface: Command, Results, and Variables windows.
• Understanding key M&E concepts: indicators, baselines, targets, and evaluation types.
• Basic Stata commands for file management and getting help.
• The structure of Stata datasets: variables, observations, and labels.
• Practical session: Navigating the Stata environment and importing a simple M&E dataset.

Module 2: Data Management and Preparation in Stata

• Importing and exporting different data formats into Stata.
• Cleaning and organizing M&E data: handling missing values, duplicates, and outliers.
• Renaming and labeling variables and values.
• Creating new variables using the generate and egen commands.
• Practical session: Cleaning and transforming a raw M&E dataset to prepare it for analysis.

Module 3: Descriptive Analysis for M&E Data

• Calculating and interpreting measures of central tendency (mean, median) and dispersion (standard deviation).
• Using the tabulate and summarize commands for data exploration.
• Creating frequency tables and cross-tabulations.
• Generating descriptive statistics for different subgroups.
• Practical session: Using descriptive statistics to create an M&E baseline report.

Module 4: Monitoring and Indicator Tracking

• Calculating key performance indicators (KPIs) and project progress indicators.
• Comparing baseline, midline, and endline data.
• Using conditional commands (if, in) to analyze specific subsets of data.
• Combining and appending multiple datasets for longitudinal analysis.
• Practical session: Tracking the progress of a project's key indicators over time and generating a progress report.

Module 5: Hypothesis Testing for Impact Evaluation

• Fundamental concepts of hypothesis testing: null and alternative hypotheses, p-value.
• Conducting t-tests to compare means between two groups (e.g., treatment vs. control).
• Performing chi-squared tests for categorical data analysis.
• Non-parametric tests for non-normal data.
• Practical session: Performing statistical tests to determine if a project intervention had a statistically significant impact on a specific outcome.

Module 6: Introduction to Regression Analysis

• Understanding the principles of linear regression in M&E.
• Fitting and interpreting a simple linear regression model in Stata.
• The purpose of regression coefficients, R-squared, and p-values.
• Checking the assumptions of linear regression using diagnostic plots.
• Practical session: Building a simple regression model to analyze the relationship between project resources and a specific output.

Module 7: Advanced Regression Models for M&E

• Running multiple regression to control for confounding variables.
• Introduction to logistic regression for binary outcome variables (e.g., project success/failure).
• Dealing with panel data (longitudinal data) using fixed effects and random effects models.
• Interpreting regression results for policy and program implications.
• Practical session: Constructing a multiple regression model to assess project impact while controlling for other factors like participant demographics.

Module 8: Qualitative and Mixed-Methods Data Analysis

• An overview of qualitative data analysis techniques in Stata.
• Using Stata's text analysis features.
• Combining quantitative and qualitative data for a mixed-methods approach.
• Triangulation of findings from different data sources.
• Practical session: Integrating qualitative survey responses into a quantitative analysis to provide richer context to the findings.

Module 9: Data Visualization for M&E Reports

• Creating effective graphs in Stata to present M&E findings.
• Generating bar charts, scatter plots, line graphs, and pie charts.
• Customizing graph aesthetics for professional presentations.
• Best practices for creating clear and informative data visualizations.
• Practical session: Creating a series of graphs to tell a compelling data story for an M&E report.

Module 10: Project-Based Application: End-to-End M&E Analysis

• A comprehensive capstone project that ties together all course modules.

• Participants will work with a provided M&E dataset from a real project.
• The project will involve data cleaning, descriptive analysis, impact assessment, and final reporting.
• Presentation of project findings and peer review.
• Practical session: Participants will work on a final project, performing a complete M&E analysis pipeline from start to finish.

Requirements:

·       Participants should be reasonably proficient in English.

·       Applicants must live up to Armstrong Global Institute admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254725012095 / +254724452588

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.

2. Invoice: We can send a bill directly to you or your company.

3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

2. Participants may cancel attendance 14 days or more prior to the training commencement date.

3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588