1. GRA 5917: Input Politics and Public Opinion Introduction GRA 5917 Public Opinion and Input Politics. Introductory Lecture, August 19th 2010 Lars C. Monkerud, Department of Public Governance, BI Norwegian School of Management

2. Introduction to GRA 5917: Iput Politics and Public Opinion, outline of lecture: purpose and goal: writing a good research paper based on thorough data analysis… 1)analysis of data: some general points… and some practical issues (Lars) 2)writing a good paper: an interesting problem, clear and consistent analysis/presentation (Rune) 3)data and statistical tools: an introduction to SPSS and central data sets (Rune and Lars in computer lab)

3. 1)analysis of data for many, if not most, problems relevant to the course subject matter we need to sensibly combine country- level data (often collected over a certain period of time) from two or more data sets… Policy = f(public preferences, institutional setup) Data set 1Data set 2Data set 3 particularily useful data sets that together can be used to analyze a number of interesting problems in course paper and/or thesis: available (w/documentation) through the course pages on It’s LearningIt’s Learning

4. 1)… and some practical issues Stay updated: activate forwarding of internal messages to e-mail adress (under Messages > Message settings)

5. 1)… and some practical issues

6. 3)data and statistical tools data sets available (w/documentation) through the course pages on It’s Learning under the PolEc Datasets folder on the leftIt’s Learning data in PolEc Datasets are identified by country-years according to one single coding scheme (i.e. not Russia- RUS which will not automatically combine, but Russia- Russia); specifically, country is indexed in the cname variable, year of measurement in year

7. 3)data and statistical tools Basic ”components” (windows) in SPSS: data sets appear in the Data Editor; output from analysis in the Viewer; (programming code in the Syntax Editor)

8. 3)data and statistical tools Variable View in the Data Editor gives information on each variable in the set: To change variables’ characteristics (e.g. labels for category codes, define values that will read as ”missing”); useful for ”getting to know” the data For covenience: to work with several data sets at a time, uncheck under Windows in Edit > Options…

9. next week’s lecture (computer lab) Procedures for data and data set manipulation and data analysis – and much else - available on the menu toolbar. Importantly, we will be looking at: 1.Outputing descriptives to get to ”know” the data/check on successfulness of data manipulation: Analyze > Descriptive Statistics > Frequencies and Analyze > Descriptive Statistics > Descriptives 2.Basic procedures to recode variables: Transform > Compute Variable 3.Procedures to aggregate data: Data > Aggregate 4.Procedures to match-merge data from two sets: Data > Sort Cases and Data > Merge Files > Add Variables