Course Objectives
This course is designed to provide trainees with the Research, Statistics, Monitoring & Evaluations skills necessary in applied research of social sciences. The course combines research design, qualitative and quantitative data management, analysis methods, monitoring and evaluations skills development, primary and secondary research design. In the process, trainees will learn about the methods and elements of designing and conducting research surveys and provide insights to address issues of monitoring & evaluations and impact assessment. Specifically, this course will impart skills to participants in the usage of basic quantitative techniques, Monitoring & evaluation. More significantly, this course also cover usage of SPSS & stata software’s for research and reporting purpose.
Course Main Topics
- QUANTITATIVE TOOLS
- Introduction to Descriptive and Inferential Statistics
- How to collect Primary Data
- Graphical Representation of Data (Bar Chart, Pie Cart)
- Introduction to measure of Central tendency (Mean, Median and Mode)
- Introduction to Measure of Dispersion (Minimum and Maximum Value, Range, Standard Deviation, Coefficient of Variation)
- Correlation and Regression
- Confidence Interval
- Hypothesis Testing
INTRODUCTION TO SPSS and STATA
- Course organization
- First sample session
- The help tool
- Log-file and do-file
- File formats in Stata
- Exercises
- Data management
- File creation, file import
- Importing data from another software (e.g. Excel)
- Managing data formats (numeric, string)
- Managing variables (e.g. drop, keep, etc.)
- Quantifiers: if, in, by
- Commands for descriptive and exploratory analysis(describe, list, summarize, tabulate)
- Exercises
- Working with Data
- Create and modify variables
- Managing missing data
- Merging files
- Exporting data and results in other formats
- Weighting data
- Exercises
- Regression and hypothesis testing
- Commands correlate, regress e rreg
- Diagnosing regression commands
- Main tools for hypothesis testing and confidence
- intervals checking (table, ttest, anova)
- Exercises
- Graphics
- Commands histogram, two-way scatter, two-way line,
- two-way connected
- Other graphical commands (box, pie, bar, qqplot)
- Using menu vs line commands
- Saving, exporting, modifying graphs
- Time formats
- Exercises
- Beyond simple regression
- Scatter plots, confidence bands and other graphical toolsto represent relations (regression)
- Time series: lagged variables creation and sample use
- Introduction to panel data
- Exercises
INTRODUCTION
- System and Impact : Input, process, output, outcome and impact
- Result based management
- Designing SMART Targets
- Supervision, monitoring, evaluation, MIS, Auditing
- Models of performance management
- Mentoring system, components, objectives and characteristics
- Monitoring indicators: Input indicators, process indicators, output indicators, outcome indicators, impact indicators.
- Qualitative and quantitative indicators
- Evaluation framework: Assessment, results measurement.
- Relevance, effectiveness, efficiency
- Impact and sustainability.
- Supervision
- Educational supervision
- Administrative supervision
- Supportive supervision
- Role of research in monitoring & Evaluation
- Data, its types and various ways of data collection
- Survey Design: Different forms of designing questions for qualitative and quantitative data collection
- Introduction of SPSS & its use in M&E
- Data and variables entry, frequency analysis
- Mean analysis, computation
- Data cleaning and dealing with missing data.
- Pivot table, cross tabulation.
- Variables comparison
- Recoding into same variables
- Recoding into different variables
- Specific cases analysis