Impact
evaluation for development projects
Impact
evaluation relies on rigorous methods to determine the changes in outcomes
which can be attributed to a specific intervention based on cause-and-effect analysis.
Impact evaluations need to account for the counterfactual – what would have
occurred without the intervention through the use of an experimental or
quasi-experimental design using comparison and treatment groups.
This
course takes you through a step by step guide towards understanding impact
evaluation for development project that is topped up by a 5 day rigorous
training of data analysis with R Statistics.
R is the language of big data—a
statistical programming language that helps describe, mine and test
relationships between large amounts of data. Learn how to Model statistical
relationships using graphs, calculations, tests, and other analysis tools.
Learn how to enter and modify data; create charts, scatter plots, and
histograms; examine outliers; calculate correlations; and compute regressions,
bivariate associations, and statistics for three or more variables.
Course
objectives
By
the end of this course, the delegates will be able to:
- Understand the value and practice of impact evaluation within the development community.
- Understand and apply a variety of quantitative methods for estimating the impact of a development program, including randomized controlled trials (RCTs), quasi-experimental designs (regression discontinuity design and difference-in-differences) and non-experimental approaches (matching and instrumental variables)
- Critically analyze impact evaluation research and gauge the validity of the findings
- Calculate the costs and benefits of different development interventions
- Calculate the necessary sample size to conduct an impact evaluation
- Analyze existing data from a development project using impact evaluation techniques
- Understanding the R language
- Building charts in R
- Descriptive and inferential statistics in R
- Hypothesis testing in R
Course
Content
a Impact
Evaluation (1 Day)
- Principles of Management and leadership
- Overview of Project Management
- Overview of Monitoring and evaluation (M & E)
- The need and importance of M & E in development projects
- Linking Project to programme and national strategies
- M&E as a Component of the Project Planning & Implementation Process
- Models of evaluation
- Planning an evaluation
- Tools for project control
- Development Project Monitoring
- Designing a Monitoring System
- Designing monitoring and evaluation indicators
- Linking your indicators to baselines, milestones and targets
- Evaluating social and institutional change
- Measuring results and impacts
·
Introducing
Impact Evaluation (2 Days)
- Why Impact Evaluation?
- Monitoring & Evaluation vs Impact evaluation
- Assessing economic, social and environmental impact
- Selecting Indicators
- Deciding Data Collection Strategies
- Developing Data Collection Instruments
- Monitoring Tools, Methods and Procedures
- Trade-offs
- Evaluation Types (process evaluation, impact evaluation)
- Clarifying Impact Evaluation Objectives
- Choosing an Evaluation Method
- Exploring Data Availability
- Developing Data Collection Instruments and Approaches.
·
Designing
an Evaluation (2 Days)
- During project identification and preparation
- During and after project implementation
- Evaluation Toolbox
- Randomization
- Regression discontinuity
- Difference in differences (double difference)
- Propensity score matching (Counterfactual Constructing Procedure)
- Instrumental variables (standard regression analysis).
- Promotion or encouragement
- Phased roll-out
- Variation in treatment
- Reflexive comparisons,
- Estimation biases when using non-experimental methods
- Integrating Quantitative and Qualitative Methods
- Endogeneity & Exogeneity
- Theory-Based Evaluation.
- Cost-Benefit or Cost-Effectiveness Analysis
- Reasons for not doing Impact evaluation
- Operational Implications
- Resource Requirements
- Use of data collection softwares
- Impact evaluation report writing
b)
Data Analysis with R Statistics (5 Days)
·
The preliminaries
o
Installing R on
your computer
o
Using RStudio
o
Familiarizing
with the R interface
o
R packages
o
The built-in R
datasets
o
Manual data entry
o
Importing data
o
Converting
tabular data to row data
o
Colours and R
o
The Colorbrewer
·
One Variable
Charts
o
Bar charts for
categorical variables
o
Pie charts for
categorical variables
o
Histograms for
quantitative variables
o
Box plots for
quantitative variables
o
Overlaying plots
o
Saving images
·
One Variable
Statistics
o
Calculating
frequencies
o
Calculating
descriptives
o
Single
proportion: Hypothesis test and confidence interval
o
Single mean:
Hypothesis test and confidence interval
o
Single
categorical variable: One sample chi-square test
o
Examining robust
statistics for univariate analyses
·
Data modification
o
Examining
outliers
o
Transforming
variables
o
Computing
composite variables
o
Coding missing
data
·
Working with the Data File
o
Case selection
o
Subgroup analysis
o
Merging files
·
Charts for
Associations
o
Bar charts of
group means
o
Grouped box plots
o
Scatter plots
·
Association
statistics
o
Correlation
o
Computing a
bivariate regression
o
Comparing means
with the t-test
o
Comparing paired
means- Paired t-test
o
Comparing means
with a one-factor ANOVA
o
Comparing
proportions
o
Creating cross
tabs for categorical variables
o
Computing robust
statistics for bivariate associations
·
Charts for Three
or More Variables
o
Clustered bar
charts for means
o
Scatter plots for
grouped data
o
Scatter plot
matrices
o
3D scatter plots
·
Statistics for
Three or More Variables
o
Multiple regression
o
Comparing means
with a two-factor ANOVA
o
Cluster analysis
o
Conducting a
principal components/factor analysis
The 10 day course
costs USD 2,100, Exclusive of a 16% V.A.T, The Cost includes all training fees,
materials, lunch and refreshments as well as certificates and 6 month post
training support.
Event
Details
|
Event Date
|
20-11-2017 8:30 am
|
|
Event End Date
|
01-12-2017 4:00 pm
|
|
Cut off date
|
15-11-2017
|
|
Individual Price
|
$2,100.00
|
|
Location
|
OpenCastLabs Training Facilities, Nairobi Kenya
|
|
Group Size
|
Rates / Day (Local) KES
|
Rates/Day (International) $
|
|
5 - 10
|
110,000.00
|
1,110.00
|
|
11 – 50
|
175,000.00
|
1,750.00
|
|
16 - 20
|
215,000.00
|
2,150.00
|
|
21 - 25
|
220,000.00
|
2,200.00
|
How
to register:
To register, send an email to: outreach@opencastlabs-africa.com You can
also visit our website on www.opencastlabs-africa.com
and fill an online application form
and submit to us.
Contact Details:
The Training Coordination Office (Joab/Diana)
Capacity Building Division
Argwings Kodhek Road, opposite YAYA Center
P.o Box 30225 - 00100 , Nairobi, Kenya
Tel: +254 0204409651 Mobile: +254 723870644
Email : outreach@opencastlabs-africa.com
Language
Participants
should be reasonably proficient in English.
Fee Exceptions
All international participants will cater for their, travel expenses,
visa application, insurance,
accommodation and other
personal expenses.
Accommodation
Accommodation
is arranged upon request. For reservations contact us below.
Payment:
Payment should be transferred through
bank 5 days
before commencement of training.
Cancellation policy
- All requests for cancellations must be received in writing.
- Changes will become effective on the date of written confirmation being received.
- The appropriate cancellation charge will apply
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