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Internal Bootcamp

13 May 2023

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Price

Free

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Intro to the Bootcamp

This bootcamp is about doing applied social science research, with an emphasis on quantitative methods. For guidance on how to articulate your research question and determine the best way to answer it, check out the IDinsight Impact Measurement Guide.

Course Content

Lesson Content

0% Complete 0/9 Steps

Intro to the Lesson

Lesson Agenda and Dataset

Lesson 1: The Stata Interface (1): Stata Windows

Lesson 2: The Stata Interface: Browse, List, Codebook

Lesson 3: Stata Syntax: Summarize, Help

Lesson 4: Stata Syntax: Tabulate

Lesson 5: Conditional Statements

Lesson 6: Generating Variables

Lesson 7: .do Files

Lesson Content

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Intro to the Lesson

Lesson 1: Principles of Writing Good .do Files (1)

Lesson 2: Principles of Writing Good .do Files (2)

Lesson 3: Macros

Lesson 4: Loops

Lesson 5: bysort

Lesson Content

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Intro to the Lesson

Lesson 1: What is Theory of Change? (1)

Lesson 2: What is Theory of Change? (2)

Lesson 3: Why is a Theory of Change important?

Lesson 4: How to Make a Theory of Change?

Lesson 5: Theory of Change Applications

Lesson 6: Theory of Change Final Thoughts

Lesson 7: Theory of Change Conclusion

Lesson Content

0% Complete 0/5 Steps

Intro to the Lesson

Lesson 1: Defining Impact and Non-Experimental Designs

Lesson 2: Randomized Evaluations

Lesson 3: Quasi-Experimental Evaluations

Lesson 4: Threats to Internal Validity

Lesson Content

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Intro to the Lesson

Lesson 1: Goals of the Lesson

Lesson 2: Example Program: Farm to Market Alliance

Lesson 3: Farm to Market Alliance Theory of Change

Lesson 4: Farm to Market Alliance Critical Theory of Change Linkage

Lesson 5: What is a Process Evaluation?

Lesson 6: What you Can and Can’t Learn from a Process Evaluation

Lesson 7: Why do a Process Evaluation?

Lesson 8: How to do a Process Evaluation

Lesson 9: When to do a Process Evaluation

Lesson 10: Wrap-Up

Lesson Content

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Intro to the lesson

Lesson 1: Why we do Statistical Inference

Lesson 2: The Central Limit Theorem

Lesson 3: Testing a Hypothesis

Lesson 4: Steps to Testing for Equality of Means (1)

Lesson 5: Steps to Testing for Equality of Means (2)

Lesson 6: One-Sample Hypothesis Tests in Stata

Lesson 7: Two-Sample Hypothesis Tests in Stata

Lesson Content

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Intro to the Lesson

Lesson 1: Simple Random Sampling

Lesson 2: Simple Random Sampling in Stata

Lesson 3: Sample Size Calculations

Lesson 4: Finite Population Correction

Lesson 5: Stratified Random Sampling

Lesson 6: Stratified Random Sampling in Stata

Lesson 7: Clustered Random Sampling

Lesson 8: Clustered Random Sampling in Stata

Lesson Content

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Intro to the Lesson

Lesson 1: What is Power? (1)

Lesson 2: What is Power? (2)

Lesson 3: Components of Power: Alpha, Delta, and Sigma

Lesson 4: Components of Power: N and Rho

Lesson 5: Individual-Level Power Calculations in Stata

Lesson 6: Clustered Designs in Stata

Lesson Content

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Intro to the Lesson

Lesson 1: Simple Random Assignment

Lesson 2: Simple Random Assignment in Stata

Lesson 3: Comparing Random Assignments

Lesson 4: Balance Tests

Lesson 5: Stratified Random Assignment

Lesson 6: Clustered Random Assignment

Lesson Content

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Intro to the Lesson

Lesson 1: Why High Quality Data is Important

Lesson 2: What Errors are we Worried About?

Lesson 3: What Leads to Errors and How to Mitigate Errors in Data Collection

Lesson 4: Example with Data

Lesson 5: Conclusion

Lesson Content

0% Complete 0/7 Steps

Intro to the Lesson

Lesson 1: Deciding What to Measure

Lesson 2: The Survey Response Process: Comprehension

Lesson 3: The Survey Response Process: Retrieval

Lesson 4: The Survey Response Process: Judgement & Estimation and Response Mapping

Lesson 5: Mitigating Social Desirability Bias

Lesson 6: Tips for Creating a Robust Questionnaire

Lesson Content

0% Complete 0/8 Steps

Intro to the Lesson

Lesson 1: Introduction to Mobile Data Collection

Lesson 2: Working with SurveyCTO

Lesson 3: Building a Survey in SurveyCTO (1)

Lesson 4: Building a Survey in SurveyCTO (2)

Lesson 5: Encryption

Lesson 6: Collecting Data

Lesson 7: Downloading Data

Lesson Content

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Intro to the Lesson

Lesson 1: The Importance of Data Cleaning

Lesson 2: Folder Structure

Lesson 3: Data Preparation: Duplicates, Renaming, Labeling

Lesson 4: Data Preparation: New Data, Missing Data, Logic Checks

Lesson 5: Data Preparation: Creating Variables, De-Identifying Data

Lesson 6: Data Transformations: Appending, Merging

Lesson 7: Data Transformations: Reshaping, Collapsing

Lesson Content

0% Complete 0/8 Steps

Intro to the Lesson

Lesson 1: Linear Regression

Lesson 2: Control Variables

Lesson 3: Clustered Standard Errors

Lesson 4: Panel Data Methods

Lesson 5: Strata Fixed Effects

Lesson 6: Heterogeneous Treatment Effects

Lesson 7: Pre-Analysis Plans

Lesson Content

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Intro to the Lesson

Lesson 1: Principles of Data Visualization

Lesson 2: Tips for Graphing in Stata

Lesson 3: Stata Graph Basics (1)

Lesson 4: Stata Graph Basics (2)

Lesson 5: Overlaying Graphs

Lesson 6: Bar Graphs

Lesson 7: Other Graphs

Lesson Content

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Intro to the Lesson

Lesson 1: Introduction

Lesson 2: Impact

Lesson 3: Costs

Lesson 4: Reporting Results

Lesson 5: Example

What African governments and their partners can do to use AI for better public service delivery

30 September 2026

Test HTML

22 September 2026

Introducing the Quality Assurance Facility for AI in Education

15 September 2026

IDinsight appoints Neha Raykar as new India Regional Director

14 September 2026

Call for Expressions of Interest: Advancing decision-relevant evidence on gig work in LMICs

2 September 2026

Building an AI-powered clinical advisor to strengthen frontline healthcare in Ethiopia

25 August 2026

Could, would, should: What philanthropy owes AI in global development

21 August 2026

Context as a public good

13 August 2026

Meeting the need for quantitative measurement in community-led development programs

7 August 2026

Ensuring responsible AI adoption in African parliaments

28 July 2026

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