Workflow of Statistical Analysis with STATA: Data Management, Analysis and Visualization
Prof. Dr. Kai-Uwe Schnapp
Dear Course Participants,
I have now uploaded an updated version of the final exercise on drive N:~. Unfortunately, Geventis does not allow to attach files to a message. If you do not have access to drive N: any more, please drop me a line at kai-uwe.schnapp@wiso.uni-hamburg.de and I will send the file direcly to you.
Deadline for delivering the excercise will be March 17th.
As I said before: If there are any questions along the way, just ask.
Best
KUS
Announcement created on: 17/02/2017 08:52
Contents STATA for Beginners, Course at the Wiso Graduate Program
Version:
June 2015
Kommentar/Inhalt |
In their education students do regularly get to know statistics to a certain extent. Ideally, some data analysis will be done with data sets ready made for teaching. The resulting knowledge of statistics differs from university to university, but usually it is sufficient for at least simple tasks in data analysis. Actually starting with an analysis of once own, however, all too often is a bit rocky. The reason for this being: Just knowing statistics is not enough. Why is that so? To being with data usually do not come as ready-made as they appear in statistics classes. They need to be adapted, transformed, aggregated or disaggregated, thoroughly documented and saved in meaning- and useful partitions. This involves a large number of tiny steps and decisions in the work process. It is all too easy to loses track of what has been done when, how, why and with which result. Why has X been filtered, why has Y been aggregated the way it has been aggregated and where does the correction in Z come from and how has it been justified? Often within days it is not clear any longer, why a variable does now look the way it does. And be it for the reason, that the seed number for some random number generator has either not even been set or at least not been saved. It gets much more inconvenient later on, when an article is ready for publication and the journal is asking for documentation or even a replication data set. Or when in interested reader is sending an e-mail, asking politely for more detailed information on data preparation and analysis. Because it is now, the search starts for information that has been lost along the way. Many of those problems can be avoided by a well thought plan for data manipulation and analysis accompanied by extensive documentation of every step in the work process. Most if not all of the things one has been doing can be kept within reach when the steps in the work process are clear (and to the extent possible standardized) and when saving and documenting becomes part of the daily routine of working with data. This course will try to introduce students to such a way of working with data and at the same time do the first steps of data manipulation and analysis with STATA. The aim is not, however, to actually teach any statistics. It is assumed that students already have at least a basic knowledge of statistics with at least some descriptive and inferential methods known to everybody. For those lacking this knowledge or not really remembering, what they learned earlier there will be a refresher in the beginning of the weak. In addition to an introduction into the graphical user interface of STATA, the structure of its command language, work process and documentation this course will teach some tricks and give hints how to deal with some problems in data manipulation and how to achieve almost directly publishable output. A special focus will be put on graphical output. |
Lernziel |
Who will get to know:
- STATA’s user interface
- basic knowledge in data handling and data manipulation with STATA
- basic knowledge oft the structure and workings of STATA’s commands for data analysis
- basic knowledge of how to quickly produce publishable output with STATA
- basic knowledge of efficient process management and documentation using STATA After all the course is a language course of sorts. You will get to know STATA as a language to code your data analysis. |
Vorgehen |
The course will be held in a computer lab. All steps will be demonstrated by the instruktor an directly applied by the students. There will be room for free but guided exercise. There will be a brief (90 minutes) intro into the Graphical User Interface of STATA for people, how did never work with STATA before in the first day of the course week. In the same day there will be two 90-minute refreshers on regression analyse and factor analysis, so that people will be able to follow data examples later in the course without much need for further explanation. |
Literatur |
As introductory literature and a good guide book for further work I suggest Kohler/Kreuter „Data analysis using STATA“ (meanwhile in its third edition) or K/K „Datenanalyse mit STATA“ (here the fourth edition from 2012 is strongly recommended) |
Hinweise zur Prüfung |
In order to earn credits students will have to complete a homework of about 5-10 hours (depending on individual work pace) with some data manipulation and analysis, the production of some output that is (almost) ready for publication and a thorough documentation of the whole process. |
-
Number of Semester Hours
2
-
Amount of Credit Points
4
-
Creditable as
-
Type of Place Allocation
Manual Place Allocation (after the registration deadline)
-
Information about Registration
–
-
Max. Number of Participants
20