Data Analysis using SPSS 2073/03/05 03/07 Bijay Lal Pradhan, Ph.D.
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Introduction to SPSS Day 1 2073/03/05 Session I Bijay Lal Pradhan, Ph.D.
Object of session I Define Statistics and SPSS Install SPSS 20 and crack Open and exit SPSS Importing and exporting data Different format of files
What is Statistics? Singular form: The process of collection, organization, presentation, analysis and interpretation of number facts. Plural form: Aggregate of facts which has different characteristics. Comparable Numerous factors effects Numerically expressed Systematically collected Purposefully collected Accurate reasonably
Introduction: What is SPSS? Originally it is an acronym of Statistical Package for the Social Science but now it stands for Statistical Product and Service Solutions One of the most popular statistical packages which can perform highly complex data organization, presentation and analysis with simple instructions.
The Three Windows: Data editor Output viewer Syntax editor
The Three Windows: Data Editor Data Editor Spreadsheet-like system for defining, entering, editing, and displaying data. Extension of the saved file will be sav.
The Three Windows: Output Viewer Output Viewer Displays output and errors. Extension of the saved file will be spv.
The Three Windows: Syntax editor Syntax Editor Text editor for syntax composition. Extension of the saved file will be sps.
The basics of managing software.
Installation of SPSS 20.0 You have software SPSS 20.0 in your computer There are two folders namely setup and crack Open setup folder and double click on application file setup. Follow the instruction and install SPSS in your computer. Don t go for licensing process. Copy "lservrc" from crack folder and paste it into the installed directory (C:\Programme\ IBM\SPSS\Statistics\20)
Opening Screen From start button click on IBM SPSS Statistics 20
Obtain the data Open your saved file with SPSS data1.sav 14
Variable descriptions Drop down menus Variable View Action buttons 15
Variable View window: Type Type Click on the type box. The two basic types of variables that you will use are numeric and string. This column enables you to specify the type of variable.
Variable View window: Width Width Width allows you to determine the number of characters SPSS will allow to be entered for the variable
Variable View window: Decimals Decimals Number of decimals It has to be less than or equal to 16 3.14159265
Variable View window: Label Label You can specify the details of the variable You can write characters with spaces up to 256 characters
Variable View window: Values Values This is used and to suggest which numbers represent which categories when the variable represents a category
Defining the value labels Click the cell in the values column as shown below For the value, and the label, you can put up to 60 characters. After defining the values click add and then click OK. Click
Measure scale?? Nominal Ordinal Scale
Nominal Gender Caste Marital status
Ordinal? First Second Third..
Scale Scale
Scales of Measure Scale Basic Characteristics Nominal Numbers identify & classify objects Ordinal Ratio Nos. indicate the relative positions of objects but not the magnitude of differences between them Zero point is fixed, ratios of scale values can be compared Examples Examples Social Security nos., numbering of football players Quality rankings, rankings of teams in a tournament Length, weight Brand nos., store types Preference rankings, market position, social class Age, sales, income, costs Permissible Statistics Descriptive Inferential Percentages, mode Percentile, median quartile deviation Arithmatic, Geometric harmonic mean range MD SD Chi-square, binomial test Rank-order correlation, Friedman ANOVA Z test, t-test, ANOVA test all other tests
Data Editor Action buttons
SPSS output viewer Drop down menus Action buttons Navigation window 28
SPSS Viewer export results 29
Syntax Editor Drop down menus Action buttons Navigation window 30
Export
Import
Import
Data management with SPSS Day 1 2073/03/05 Session II
Practice 1 Construct the following variables in the variable view on the basis of following information A study was conducted to know the attitude of a bank s customer towards the bank. The question asked to the customer was: Do you feel safe in your transactions with the bank? The respondents were to answer the question on a seven-point scale (1 = Strongly Disagree, 7 = Strongly Agree). There were other variables mentioned below on which data was collected.
Other variable 1. Sex of the respondent Male - M Female - F 2. Marital status Married - M Single - S 3. Income of the respondent (in rupees) 4. Age of the respondent (in years) 5. Educational background of the respondent Below higher secondary - 1 Higher secondary - 2 Graduation - 3 Post graduation - 4
Click
Entering Data Copy paste can be done to copy it from word to SPSS. First copy paste in to MS Excel and then to SPSS. Save the data in Excel and import to SPSS Or save in CSV format then to SPSS
Variable/Case in and out Entering new variable Deleting the existing variable Entering new case Deleting the existing cases
Saving the data To save the data file you created simply click file and click save as. You can save the file in different forms by clicking Save as type. Click
Sorting the data Click Data and then click Sort Cases
Sorting the data (cont d) Double Click Name of the students. Then click ok. Click Click
Transforming data Click Transform and then click Compute Variable
Transforming data (cont d) Example: Adding a new variable named corrected_ci which is corrected confidence interval Type in corrected_ci in the Target Variable box. Then type in 8-CI in the Numeric Expression box. Click OK Click
Transforming data (cont d) In the same way find the log(income) Type in ln_income in the Target Variable box. Then type in lnincome in the Numeric Expression box. Click OK In the similar manner Create a new variable named sqrtage which is the square root of age.
Visual Binning Visual Binning is the process of arranging data in a suitable class. So that we can tabulate data and can be drawn conclusion from the scale type of data.
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