About the Course: Data Analysis course is intended for developmental participants interested in learning the most effective data analysis methods to solve problems and achieve insight. This course will focus on how to plan, carry out, and communicate analyses of real data sets. This course introduces statistical techniques such as summarizing and presenting data, estimation, probabilities and probability distributions, confidence intervals, correlation and regression models and hypothesis testing. This course places special emphases on the understanding of key concepts and statistical thinking, calculations and interpretation of results. Course Format: The course will consist of interactive onsite lectures. The lectures will begin with theory introduction and its real world application followed by practical session on STATA. Participants are encouraged to share their data sets for use during the practice sessions however; the facilitator will share course data set and lecture slides in advance. Learning Outcomes:          Present different types of data in an appropriate manner. Perform statistical analysis. Present findings of data analysis in a research proposal. Identify areas/issues/situations where statistical analysis would be beneficial. Collect, analyze and interpret data relevant to their decision-making. Identify and interpret trends. Use STATA to calculate statistical measures and interpret STATA outputs. Understand how to apply relevant statistical techniques to solve the underlying problems/issues. Report on statistical findings COURSE MODULES:     Research/Evaluation Design Data Collection Methods, and Introduction to STATA Introduction to Data Analysis, Types of Data, Data Measurements, Descriptive Statistics, Proportions, Rates, Ratio’s, Percentages, Central Location, Dispersion, Shape of Distribution, Display of data frequency tables, charts and graphs Introduction to probability Hypothesis Testing 1: Significance Testing (P-value) and Point Estimates (CI) Sampling and Sampling errors Probability Distribution (Binomial/Poisson) Cross-tabulation and Correlation Hypothesis Testing 2: Simple Regression Hypothesis testing for Multiple regression model Survival analysis Training Format: All materials are made available through In-Class-Learning Approaches. Approximately 6 hours time commitment of your time per day. Daily feedback from committed instructors. Participants are expected to submit daily assignments to earn certificate of completion Exercises: After they have read the material for each unit, participants are expected to test their own Learning by completing some relevant exercises and tasks . Assignments: In order to demonstrate their understanding of the course content, Participants will be required to submit Four assignments. DURATION AND COURSE LOAD: 5 Days - 8 hours per day. PARTICIPANTS: Researchers, M&E Professionals, Data Analysis and would be researchers and data analysts. COURSE FEE: $500 per participants GENERAL COURSE CONTACT: Please contact Ms. Farzana Ahamadi, Training Coordinator, at [email protected] for further information and course registration.