Using SPSS in Education Part 1
- 2. ” “There are three types of lies — lies, damn lies, and statistics. …Benjamin Disraeli(1804 — 1881)
- 3. SPSS — Statistical Package for Social Sciences Now: IBM SPSS — Statistical Product and Service Solutions
- 4. Is SPSS the answer to all your problems? Released in its first version in 1968 after being developed by Norman H. Nie, Dale H. Bent, and C. Hadlai Hull The original SPSS manual has been described as one of "sociology's most influential books" for allowing ordinary researchers to do their own statistical analysis The layman considers SPSS as a magic wand – one that would do all statistical analyses, plot neat graphs, interpret the results, all by a few mouse clicks In fact, SPSS is one of the most user-unfriendly software, with a steep learning curve, perplexing interface and complex outputs. It is confusing even with a good user manual, and almost unusable without one. It gives more than we desire, and for that it gives more choices than we can handle – yet it is still one of the best software
- 8. Common Types of Analysis 1. Description 2. Comparison 3. Correlation/Association
- 9. Descriptive Analysis The world is full of information (2 exabytes or 2 billion gigabytes of new information is created each year) The mountains of raw numbers have to be intelligently summarized to make them meaningful Descriptive analysis simply summarises the sample It could be either in tabular form or in graphical form Descriptive analysis includes Percentages Measures of Central Tendency (Mean, Median, Mode) Measures of Variability or Dispersion (SD, range, kurtosis, skewness)
- 10. Inferential Analysis It is drawing conclusions from the data – though testing hypotheses and/or making estimations Technically, Inferential statistics is concerned with making predictions or inferences about a population from observations and analyses of a sample We can take the results of an analysis using a sample and can generalize it to the larger population that the sample represents To address this issue of generalization, we have tests of significance A Chi-square or t-test, for example, can tell us the probability that the results of our analysis on the sample are representative of the population that the sample represents Examples of inferential statistics include linear regression analyses, logistic regression analyses, ANOVA, correlation analyses, structural equation modeling, and survival analysis, to name a few
- 11. Plan your Data Decide what variables you need and document them It is a good practice to create a data codebook during planning stage You can use Excel to key in data It can then be exported to SPSS
- 12. Sample Data Coding Variable Name Label Type (Width) Value Codes Missing Code ID Identification String (4) None Not allowed GEN Gender Numeric (1.0) 0 = "Male" 1 = "Female" EdQua Educational Qualifications Numeric (1.0) 0 = "Higher Secondary" 1 = "Graduate" 2 = "Post Graduate" 3 = "M.Phil./Ph.D." -99 ProfQua Professional Qualifications Numeric (1.0) 1 = "BTI/BTC" 2 = "D.Ed./D.El.Ed." 3 = "B.Ed." -1 Post Post Numeric (1.0) 0 = "Head Master" 1 = "Teacher" 2 = "Assistant Teacher" 9 Loc Locality 0 = "Urban" 1 = "Rural" Age Age Group Numeric (1.0) 0 = "Under 30 Years" 1 = "30 and 40 Years“ 2 = "Over 40 Years" Blank, "." Or AtRtE Awareness Towards RtE Act Numeric (2.0 None 11/11/1111 JSS Job Satisfaction Numeric (2.0) None -99
- 13. Tips for Data Entry in Excel 1. Row 1 of your Excel spreadsheet should contain only variable names. Do not extend names to row 2. 2. Each subsequent row (line) in the Excel spreadsheet should contain data for a single subject or observed entity. 3. Avoid blank rows — it will complicate your import and analysis. 4. If you have missing data in your data set, define a missing value code and place that code in any cell that contains missing data. 5. Always use date variables with four-digit year formats in Excel. 6. Use your data dictionary, making sure to include all of the variables you will need. 7. If you have the time or resources, enter your data twice (preferably using two different data entry people) and compare the two files.
- 14. Data in Excel
- 15. Importing & Using Excel Data
Editor's Notes
- #6: Statistical Analysis: Quick Reference Guidebook, Sage Publications, 2007, 260 Pages, 73 Tables, 50 Figures 8 Chapters Including Describing/Examining Data., Comparing 1 or 2 Means using t-Test, Correlation & Regression, analysis of Categorical Data (Contingency Table), ANOVA, ANCOVA, Non-Parametric Analysis, Regression Contains Appropriate Application for the tests, Tips, and even reporting procedure Does not have examples from Education