spss-anintroduction-150704135929-lva1-app6892.ppt
- 2. What is SPSS? Originally it is an acronym “Statistical Package for the Social Sciences” but now it stands for Statistical Product and Service Solutions It is also known by the name PASW (Predictive Analytics Software) It is a software used for data analysis in business research. Can be used for: o Processing Questionnaires o Reporting in Tables and Graphs o Analyzing: Means, Chi-square, Regression, …and much more..
- 3. History SPSS has a long heritage Introduced in 1968. Was originally developed to facilitate statistical analysis in the social sciences. Early versions designed to run on mainframe computers. On July 28, 2009 IBM announced it was acquiring SPSS Inc. for $ 1.2 billion in cash The current versions (2015) are officially named IBM SPSS Statistics.
- 4. About SPSS Incorporated SPSS Inc. is a leading worldwide provider of predictive analytics software and solutions. SPSS Inc. was a software house headquartered in Chicago and incorporated in Delaware The company was started in 1968 by Norman Nie, Dale Bent, and Hadlai "Tex" Hull Today SPSS has more than 250,000 customers worldwide, served by more than 1,200 employees in 60 countries.
- 5. Now the company is known as SPSS: An IBM® Company :
- 6. General Capabilities SPSS has a lot of great features Can import data from many different sources, such as Microsoft® Excel and SAS®. Provides analysis tools to generate reports, charts, plots, descriptive statistics, and run advanced statistical analyses. In addition to user interface, provides a command syntax that can simplify certain things, such as running repetitive tasks.
- 7. Basic Operations in SPSS (Basic Steps In Data Analysis) Variable Entry (adding or deleting a variable) Data Entry (adding or deleting the data) Saving the data Importing data from Excel file Checking the data entered Sorting the data Transforming the data 7
- 8. Variables A concept which can take on different quantitative values is called a variable. Ex. What are variables you would consider in buying a second hand bike? Brand Type Age Condition (Excellent, good, poor) Price 8
- 9. Dichotomous variables (having two values only) Yes or No Male or Female Income, age or a test score are the examples of continuous variables. These variables may take on any value within a given range, or in some cases, an infinite set. 9
- 10. Measurement Scales The process of assigning numbers to objects in such a way that specific properties of the objects are faithfully represented by specific properties of the numbers. Types of Scales: Nominal Ordinal Scale Interval Ratio 10
- 11. Types of Scales Nominal example: nationality, race, gender… based on a concept (two categories variable called “dichotomous nominal”) Ordinal example: knowledge, skill... (more than, equal, less than) rank-ordered in terms of a criterion from highest to lowest Interval/Ratio example: age, income, speed... based on arithmetic qualities and have a fixed zero point
- 12. 7 3 8 Nominal Numbers Assigned to Runners Ordinal Rank Order of Winners Interval Performance Rating on a Scale Ratio Time to Finish in Seconds Third place Second place First place Finish Finish 8.2 9.1 9.6 15.2 14.1 13.4 Scale
- 13. Scale Basic Characteristics Common Examples Nominal Numbers identify & classify objects Gender, numbering of football players Percentages, mode Chi-square, binomial test Ordinal Nos. indicate the relative positions of objects but not the magnitude of differences between them Quality rankings, rankings of teams in a tournament Percentile, median Rank-order correlation, Friedman ANOVA Ratio Zero point is fixed, ratios of scale values can be compared Length, weight Geometric mean, harmonic mean Coefficient of variation Permissible Statistics Descriptive Inferential Interval Differences between objects Temperature (Fahrenheit) Range, mean, standard Product- moment Primary Scales
- 14. SPSS INTERFACE
- 15. TYPES OF WINDOWS Data view Variable View Output Viewer Pivot Table Editor Chart Editor Text Output Editor Syntax Editor
- 16. Data Editor (.sav files) The Data Editor lets you see and manipulate your data. You will always have at least one Data Editor open (even if you have not yet opened a data set). When you open an SPSS data file, what you see is a working copy of your data. Changes you make to your data are not permanent until you save them (click File - Save or Save As). Data files are saved with a file type of .sav, a file type that most other software cannot work with
- 17. Data Viewer Entering Editing Displaying DATA No. of Respondents/Questionnaires/Schedules
- 18. DATA VIEW
- 19. VARIABLE VIEW In the Variable View you can see and edit the information that defines each variable (sometimes called meta-data) in your data set: each column of the Data View is described by a row of the Variable View.
- 23. 1. Opens automatically if it runs a procedure 2. Displays Statistical results, Graphs and save it for future use. Outline Pane Navigate output Highlight output Pivot table editor Text output edit Chart Editor
- 24. Pivot table Editor Text Edit
- 26. Syntax
- 27. Manually Entering Data SPSS makes it easy. Start with the Data Editor. There are two tabs at the bottom: Data View Variable View Gives you two ways to enter data: Start with Data View and just start typing! Start with Variable View and define your variables first. Think of variables as labels that describe your data.
- 28. Gender Age