Training modules
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Stata training (60 hours)
1. Introducing Stata software
1.1 Generals about Stata
1.2 General appearance of the Windows interface
1.3 Stata’s Toolbar
1.4 Help on Stata
2. Stata Databases
2.1 Creating a database in Stata
2.2 Conversion of a stata-readable database with StatTransfer
2.3 Importing a database into Stata
2.4 Type of variables in a Stata database
2.5 Data mining
2.6 Export of a database
3. Working with Stata
3.1 Directories
3.1.1 The work directory
3.1.2 Creating a directory
3.1.3 Directory Change
3.2 Functions and expressions
3.2.1 Arithmetic Operators
3.2.2 Expressions by, if and in
3.2.3 Relationship Operators
3.2.4 Functions
3.2.5 Logic Operators
3.3 Files do and log
3.3.1 Creating a do file
3.3.2 Comment from a do file
3.3.3 Creating a log file
3.4 Variable Management Orders
3.4.1 Creating new variables: generate and egen commands
3.4.2 Other Variable Management Orders
3.4.3 Abbreviations of variable names and commands
3.4.4 Putting labels for variables
3.4.5 Putting labels for the values of a category variable
3.5 Macros and System Values
3.5.1 Creating and using a global macro
3.5.2 Creating and using a local macro
3.5.3 System Values
3.6 Data cleaning/cleaning
3.7 Missing data
3.8 Database merger
3.9 Descriptive statistics
3.9.1 Summarize command
3.9.2 Tabulate control
3.9.3 Correlation coefficients
3.9.4 Collapsing command
3.9.5 Some other descriptive statistics orders
3.9.6 Data Weighting
3.10 Statistical tests
3.10.1 Average comparison test
3.10.2 Variance comparison test
3.10.3 Proportion comparison test
3.10.4 Chi Test 2
3.10.5 Spearman test
3.11 Cross-sectional data regressions
3.11.1 The Linear regression model
3.11.2 The logit model
3.11.3 The probit model
3.11.4 Some other regression models and their Stata controls
3.11.5 Export of regression results
3.12 Charts
3.12.1 Histograms
3.12.2 Column and band diagrams
3.12.3 Sector charts or camemberts
3.12.4 The point cloud
3.12.5 Mustache boxes
3.12.6 Two-dimensional charts
3.12.7 Export of charts
3.13 Loops
3.13.1 The Principle
3.13.2 Application
3.14 The dies
3.14.1 Definition of dies
3.14.2 Operations on dies
3.14.3 Matrix export
3.15 Adding new modules to Stata
Survey survey theory and practice training (40 hours)
1. Generals on Statistics
1.1 Some definitions (universe, statistical units, survey, sample, variables, etc.)
1.2 Estimator, random variable, survey base
1.3 Qualities of a survey (precision research, notion of representativeness, errors of observation)
2. General investigations
1.1 Goals
1.2 The main collection units
1.3 Key concepts used in surveys
1.4 Electronic collection
3. Organization of information-gathering operations
3.1 The general design of the survey
3.2 The development of the questionnaire and guides
3.3 Organizing and conducting fieldwork
3.4 Processing survey data
3.5 The dissemination of results
4. Empirical sampling methods
4.1 The quota method
4.2 The Route method
5. Simple random polls
5.1 Estimator calculation in a simple random survey (average and total estimators, variance calculation, relative standard error, estimate of proportion, estimate by confidence interval)
5.2 Determining the sample size of an SAS (budgetary constraint, precision constraint, consideration of non-responses in determining sample size)
5.3 Procedure for drawing units in an SAS (systematic drawing, method criticism)
6. Uneven probability polls
6.1 Principle
6.2 Definition of inclusion probability
6.3 Estimator calculation
6.4 Drawing methods
7. Laminated surveys and non-response treatment
7.1 Principle and objectives
7.2 Estimation formulas (estimate of average, total and proportion, calculation of accuracy)
7.3 Strata choice
7.4 Sample and distribution between strata
7.5 Non-answers
8. Multi-degree polls
8.1 Principle and ratings
8.2 Calculating and properties of the probabilities of inclusion of secondary units
8.3 Total Estimator: General case
8.4 Practical terms of drawing a two-degree sample and calculating estimators
8.5 The Cluster survey
Training to develop CAPI applications with Survey Solutions (60 hours)
SPSS training (60 hours)
Impact assessment training (30 hours)
1. What is impact assessment ?
1.1 Impact definition
1.2 Correlation and causality
1.3 Impact Assessment Goals
1.4 Definition of impact assessment
1.5 Utility of impact assessment
2. Relationship between monitoring and assessment and impact assessment
3. Counterfactual
3.1 Definition
3.2 Criteria for building a good counterfactual
3.3 Bad approaches to building a counterfactual
4. The methods of impact assessment
4.1 Experimental Method or Randomization
4.1.1 Definition and Benefits
4.1.2 Randomization Procedure
4.1.3 Different randomization levels and units
4.1.4 External validity and internal validity
4.1.5 Threats to internal validity
4.1.6 Determining the sample size of an impact assessment
4.2 Quasi-experimental methods
4.2.1 The double difference
4.2.2 The discontinuity of regression
4.2.3 Pairing
5. Case studies
Geomatics training, with ArcGIS and QSIS (40 hours)
