Technical and Substantive Skills

Statistical Refresher using STATA - Data Analysis using STATA -
Date:		13 November, 20 November and 27 November 2012
		or
		15 November, 22 November and 29 November 2012
Time:		13:00 - 16:00
Venue:		IT Learning Lab, UNESCAP Learning Centre
Facilitator:		Professor Yong Yoon Assistant Dean and Chairperson of Ph.D. Program in Economics, Faculty of Economics, Chulalongkorn University, Bangkok, Thailand
Target audience:		Staff members interested in working with data more effectively and in enhancing their skills to perform quantitative and statistical analyses
Prerequisites:		"STATA for All" or experience reading and reorganizing data, conducing simple analyses and constructing tables and figures using STATA or a similar programme.

An introduction to STATA:

What is STATA?

STATA is a powerful tool for data management, statistical analysis and model building. Learning how to use STATA well should be, in practical terms, invaluable for ESCAP's staff whose work is related to the statistical analysis of data. This second training course (a follow up of “STATA for ALL”) is aimed at the novice user to provide practical knowledge and understanding of the analytical tools provided by STATA beyond just data manipulation that should enhance statistical understanding and capacity for analytical data work and interpretation using STATA.

Objectives:

After successfully completing this second STATA session (also three 1/2-day training modules), which will include real data examples and an independent project, participants will be able to better understand and conduct proper statistical analyses using STATA.

Topics:

Day 1: Statistics using STATA

Basic descriptive statistics Controlled-experiments versus observational studies Estimation and hypothesis testing One sample tests (t-test) Two sample tests (test for the difference in means) ANOVA (one-way and two-way)

Day 2: Regression analysis using STATA

Correlation and simple regression (OLS) Multiple regression (OLS) Post-estimation diagnosis (checking OLS assumptions) Data manipulation and transformation Common errors in regression analysis Brief introduction to other methods (logistic, panel, time-series)

Day 3: Practice session

Participants will be assigned a project to be completed in small groups or individually with the objective of solidifying understanding of the topics covered in the previous two sessions.

For more information on the session, contact Mr. Alberto Isgut (MPDD) ext. 1773