![]() 44 Task 20 Excluding observations Select cases. 42 Task 19 Analysing data in subgroups - Split File. 40 Adding cell percents and the chi-square statistic. ![]() 33 Task 15 Producing a bar chart from frequencies. 31 Task 14 Using summary statistics for continuous variables the Descriptives procedure. 29 Task 13 Procedure commands - Frequencies. ![]() 21 Frequency tables - the frequencies procedure. PrerequisitesBasic familiarity with Windows and at least an elementary knowledge of simple statistics such as t-tests, chi squared tests, p values and confidence intervals would be useful (statistical theory is not taught on this course).ĬontentsDocument information Task 1 Task 2 Task 3 Task 4 Task 5 Practical exercise in Data Preparation. This document uses version 16 of SPSS for Windows. IntroductionSPSS provides facilities for analysing and displaying information using a variety of techniques. Introduction to SPSS (version 16) for Windows (March 2010) 2010 University of Bristol. Related documentationOther related documents are available from the web at: There is no introduction to STATA documentation produced by Information Services, but there are short courses on STATA available within the University of Bristol provided by the Department of Social Medicine. To find these, go to and in the Keyword box, type the document code given in brackets at the top of this page. Introduction to SPSS (version 16) for Windows (spss16-2)ĭocument informationCourse filesThis document and any associated practice files (if needed) are available on the web. University of Bristol Information Services document spss16-2 This includes being able to: create frequency tables produce bar charts use crosstabulation and correlation move data from other applications into SPSS move SPSS output into your word processor application. Introduction to SPSS (version 16) for WindowsPractical workbookĪims and Learning ObjectivesBy the end of this course you will be able to: get data ready for SPSS create and run SPSS programs to do simple statistical data analysis.
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