1. Introduction to SPSS (Version 16) OMID MINOOEE MBA (ABM),second semester Institute of development study Mysore university
2. content:SpssSPSS at a glanceBasic Structure of SPSSCleaning your dataDescriptive StatisticsChartsData manipulationOther Resources
3. spssSPSS is a computer program used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, statistical analysis, and collaboration and deployment (batch and automated scoring services).
4. Ownership history: Between 2009 and 2010, the premier vendor for SPSS was called PASW (Predictive Analytics Software) Statistics. The company announced on July 28, 2009 that it was being acquired by IBM for US$1.2 billion. As of January 2010, it became "SPSS: An IBM Company". Complete transfer of business to IBM was done by October 1, 2010. By that date, SPSS: An IBM Company ceased to exist. IBM SPSS is now fully integrated into the IBM Corporation, and is one of the brands under IBM Software Groups Business Analytics Portfolio, together with IBM Cognos.
5. Statistics program: SPSS (originally, Statistical Package for the Social Sciences) was released in its first version in 1968 after being developed bynoH. Nie and C. Hadlai Hull. SPSS is among the most widely used programs for statistical analysis in social science. It is used by market researchers, health researchers, survey companies, government, education researchers, marketing organizations and others. The original SPSS manual (Nie, Bent & Hull, 1970) has been described as one of "sociologys most influential books
6. SPSS at a glance SPSS stands for Statistical Package for the Social Sciences SPSS was made to be easier to use then other statistical software like S- Plus, R, or SAS. The newest version of SPSS is SPSS 17.0. Today we will be working on SPSS 16.0.
7. How to open SPSSGo to STARTClick on PROGRAMSClick on SPSS INCClick on SPSS 16.0
8. Opening a data fileClick on FILE OPEN DATAClick MY COMPUTER LOCAL DISK C:/Click PROGRAM FILES SPSSClick TUTORIAL SAMPLE FILESSelect CATALOG.SAV
9. Basic structure of SPSSThere are two different windows in SPSS1st – Data Editor Window - shows data in two forms Data view Variable view2nd – Output viewer Window – shows results of data analysis *You must save the data editor window and output viewer window separately. Make sure to save both if you want to save your changes in data or analysis.*
10. Data view vs. Variable viewData view Rows are cases Columns are variablesVariable view Rows define the variables Name, Type, Width, Decimals, Label, Missing, etc. Scale – age, weight, income Nominal – categories that cannot be ranked (ID number) Ordinal – categories that can be ranked (level of satisfaction)
11. Cleaning your data – missing dataThere are two types of missing values in SPSS: system-missing and user-defined.System-missing data is assigned by SPSS when a function cannot be performed. For example, dividing a number by zero. SPSS indicates that a value is system-missing by one period in the data cell.
12. Cleaning your data – missing data User-defined missing data are values that the researcher can tell SPSS to recognize as missing. For example, 9999 is a common user-defined missing value. To define a variable’s user-defined missing value…Look at your variables in VARIABLE VIEWFind the column labeled MISSINGFind the variable that you would like to workwith.Select that variable’s missing cell by clickingon the gray box in the right corner.click DISCRETE MISSING VALUESenter 9999 to define this variable’s missingvalueA range can also be used if you only wantto use half of a scale.
13. Cleaning your data – missing data cont.When you have missing data in your data set, you can fill in the missing data with surrounding information so it does not affect your analysis. click TRANSFORM click REPLACE MISSING VALUES select the variable with missing values and move it to the right using the arrow SPSS will rename and create a new variable with your filled in data. click METHOD to select what type of method you would like SPSS to use when replacing missing values. click OK and view your new data in data view
14. Descriptive Statistics Lets say we are interested in learning more about the number of customer service representatives (service). Click ANALYZE Click DESCRIPTIVE STATISTICS Click FREQUENCIES Choose service from the list.
15. Descriptive Statistics continued Lets learn more about the number of catalogs mailed (mail). Click ANALYZE Click DESCRIPTIVE STATISTICS Click DESCRIPTIVES Move MAIL over with the arrow Click OPTIONS – we can choose which statistics we are interested in looking at We should remember that these descriptive statistics will not always make sense for every variable. For example, we should not be asking for the mean of nominal variables like gender or race.
16. Graphing Data Click GRAPH Click CHART BUILDER Click HISTOGRAM Put MEN on the X axis. Click ELEMENT PROPERTIES. Check the box labeled DISPLAY NORMAL CURVE. This will impose a normal curve onto your graph. You can also change the style of your graph in this element properties window. You can copy and paste these graphs into word and excel files.
17. Graphing Continued There are other ways to make graphs. Click ANALYZE Click DESCRIPTIVE STATISTICS Click FREQUENCIES Click services Click CHART Click BAR CHART Click PERCENTAGES
18. Data manipulation – select casesBy selecting cases, the researcher can select only certain cases for analysisclick DATAclick SELECT CASESclick RANDOM SAMPLE OF CASESselect your preferences
19. Data manipulation – compute new variable Computing new variables – create a new variable from multiple variables click TRANSFORM click COMPUTE fill in the new target variable TOTALSALES fill in numeric expression = men+women+jewel create an IF statement by clicking on the IF button click INCLUDE IF CASE SATISFIES CONDITION enter condition MAIL>10000 This new variable TOTALSALES tells us what the total sales are for catalogs which mailed over 10,000 catalogs.
20. Data manipulation in action!Try creating another variable for TOTALSALES2 for catalogs which mailed under 10,000 catalogs.Try comparing the descriptive statistics of TOTALSALES and TOTALSALES2.What did you find?
21. Data manipulation – recode a variableRecoding allows a researcher to create a new variable with a different set of parametersclick TRANSFORMclick RECODE INTO DIFFERENT VARIABLEmove mail over to the rightcreate a name for the new variable mailcategoriesclick OLD AND NEW VALUES
22. Data manipulation – recode a variable cont.click RANGE to create ranges of old valuesclick VALUE to create a new value for that range
23. Data manipulation in action!Try recoding another variable on your own.Try finding the descriptive statistics of your new variable.
24. Data manipulation – create a dummy variableDummy variables is a variable that has a value of either 0 or 1 to show the absence or presence of some categorical effect To create a dummy variable… click TRANSFORM click RECODE INTO DIFFERENT VARIABLE click OLD AND NEW VALUES click RANGE to create range of old values click VALUE to set new value to 0 or 1
25. What we have learned!SPSS at a glanceBasic Structure of SPSSCleaning your data – missing dataDescriptive Statistics – frequencies, descriptive statisticsChartsData manipulation – select cases, recoding, dummy variables