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In latest version of SPSS we have another option in menu bar that is ADD-ONS
In the next we can c the frequency table of the Gender here Percent include the all values. Valid Percent exclude the missing values.
Nominal. For nominal data (no intrinsic order, such as Catholic, Protestant, and Jewish), you can select Phi (coefficient) and Cramér's V, Contingency coefficient, Lambda (symmetric and asymmetric lambdas and Goodman and Kruskal's tau), and Uncertainty coefficient.Ordinal. For tables in which both rows and columns contain ordered values, select Gamma (zero-order for 2-way tables and conditional for 3-way to 10-way tables), Kendall's tau-b, and Kendall's tau-c. For predicting column categories from row categories, select Somers' d.
The t-statistic was introduced in 1908 by William Sealy Gosset
Statistical Package for Social Science (SPSS)
Presented By:Shikha Sharma
SPSS stands for Statistical Package for the SocialSciences SPSS Incorporated is a leading worldwide providerof predictive analytics software and solutions. First version of SPSS was released in 1968, afterbeing developed by Norman H. Nie, Dale H. Bentand C. Hadlai Hull.. The company announced on July 28, 2009 that itwas being acquired by IBM for US$1.2 billion.
Company LogoSPSS is now owned by IBM.Between 2009-10 the primer Venderof SPSS was called PASW (PredictiveAnalytics SoftWare) .IBM SPSS Statistics 21.0 – Released onAugust 2012 Latest version
With SPSS we can analyze data in three basic ways:Describe data using descriptive statistics examplefrequency, mean, minimum and maximum.Examine Relationships between variables examplecorrelation, regression, factor analysis etc.Compare groups to determine if there are significantdifference between these groups example t-test,ANOVA etc.
Go to START Click on PROGRAMS Click on SPSS INC Click on SPSS 16.0
There are two different windows in SPSS 1st – Data Editor WindowIn data editor we can create variables, enter dataand carry out statistical functions. 2nd – Output Viewer WindowOutput window shows what results are producedby analyzing the functions.
Data Editor WindowConsists Two TABsData ViewVariable View
Data view is used to enter data and viewdata. In data view:◦Rows represent individual cases. It canbe state, company, business etc.◦Columns represent particular variable inyour data file.
11CasesVariablesToggle betweenData and VariableViewsValue labels
Variable View is used to create and definevarious variables. In Variable View:◦ Row represent individual variable or definethe variable◦ Column represent the specific characteristicof variable like Name, Type, Width,Decimals, Label, Missing, Align, Measureetc.
The file menu SPSS containsstandard option like other programs. File menu allows creating new files,open existing files, save files, readtext data, print, print preview, exitfrom SPSS and other basic activities
The edit menu allows thestandard functions like tocut, copy, paste, edit, redo andundo. It has some other functions likeInsert variable/case, Go tovariable/case and Edit SPSSpreference by OPTION
The view menu allow usto activate/deactivate theStatus bar and othertoolbars. We can change fonts,gridlines, value labelsand see variables.
The data menuallows us to definevariable properties,dates, sorting cases,sorting variables. We can merge files,split a file, selectcases and weightcases.
The transform menuallows creating newvariables usingcompute variable. Helps in changingvariables in the datafile through recode,rank cases etc. Create time series,date & time wizard,replace missingnumbers etc.
The analyzemenu allowsthe analysis ofdata with helpof variousstatisticaltools &techniques.
The graphs menuallows us to createbar chart, line chart,area chart, pie chart,histogram, scatterplots along withmany othervariations. This option can beused when we wantto produce graphwithout any analysisof data.
The utilities menuhelps in usingvarious otherutilities, which maybe not required innormal usage.
Add-ons are programs that can beadded to the base SPSS package whichprovides a list of various featuresrequisite for special requirements andare mostly meant for advanced levelusers. It include options like forecasting,advanced statistics, decision trees andmany more options.
Window can be used to selectwhich window you want to view(i.e., Data Editor, Output Viewer, orSyntax). Since we have a data fileand an output file open, let’s trythis. Select Window/Data Editor. Thenselect Window/SPSS Viewer.
Help has many useful options including alink to the SPSS homepage, a statisticscoach, and a syntax guide. Using topics,you can use the index option to type in anykey word and get a list of options, or youcan view the categories and subcategoriesavailable under contents. This is anexcellent tool and can be used totroubleshoot most problems.
Before you can analyze data, you need somedata to analyze.To open a data file:Step 1: From the menus choose: FileOpenData...
Now in next step it opens theOPEN FILE DIALOG BOX
Now we select the Employee data file to open from theOpen File Dialog Box
Alternatively, you can use the Open File button onthe toolbar.Open File toolbar buttonThis opens the Open File dialog box.
The Analyze menu contains a list of generalreporting and statistical analysis categories.Most of the categories are followed by anarrow, which indicates that there are severalanalysis procedures available within thecategory; they will appear on a submenuwhen the category is selected. Well start with a simple frequency table (tableof counts).
From the menus choose:Step 1: Select AnalyzeStep 2: Select DescriptiveStatisticsStep 3: Select FrequenciesNow……..
In the dialog box, youchoose the variablesyou want to analyzefrom the source list onthe left and move theminto the Variable(s) liston the right. Click Gender [gender]in the source variablelist, and then click theright-arrow button tomove the variable intothe target Variable(s)list.
Click Employmentcategory [jobcat] inthe source list, andthen click the rightarrow button again. Click OK to run theprocedure.
Output window shows theresult that are produced byanalyzing the functions.The output window isbroken in two parts:Left part: Outline ofOutput PaneRight part: Result ofAnalysisLeft PartRight Part
First open SPSS through above procedure andin the window click Type in data Click OK
Example: A close ended questionnaire isdeveloped to know the choice foreducational courses• Information required related to variables: Unique ID,Name, Age, Sex, Educational Qualification, EducationalCourse Preference.• First Define VariablesVariable view– Name– Type (Numeric)– Width– Decimal– Label– Values (= the codes of the answers)– Measure (= Level of Measurement Nominal, Ordinal, Scale)
Click on the cell Valuelabel. Some dotted lines willappear ahead of “None”Click those lines, a new boxwill pop up i.e. Value LabelsDialog Box as on right.Type Value Code in ValueBox and type value labelClick ADD.Then OK
Another Example of Value Label forVariable : Educational Qualification
The Descriptive procedure displays univariatesummary statistics for several variables in asingle table and calculates standardizedvalues (z scores). Variables can be ordered bythe size of their means (in ascending ordescending order), alphabetically, or by theorder in which you select the variables (thedefault).
Procedure of Descriptive Analysis• .• To run a Descriptive analysis,from the menus choose:• AnalyzeDescriptive StatisticsDescriptives...
• Now the dialog boxappears.• Now Select the variablePrevious Experience inthe left side box byclicking the right arrowbutton between thetwo boxes.• The variable will shift tothe right side inVariable(s) list.
Procedure of Descriptive Analysis• Select Options from theDescriptive Option dialogbox.• For example: Mean,Minimum, Maximum &Standard Deviation.• Now CLICK Continue.
Procedure of Descriptive Analysis• Click OKtab.
Output of Descriptive Analysis in OutputWindow
How to Save the Output……..• Now Click on the FILEMENU• SELECT the option Savethe dialog box appears.• Click the Tab Save.
* Analysis of Variance (ANOVA) was introduced by thenoted statistician R.A. Fisher in 1920. A one-wayanalysis of variance (ANOVA) is used when youwant to compare the mean scores of more thantwo groups. One-way ANOVA is employed when youhave one independent grouping with three or morelevels or groups and one dependent continuousvariable.ANOVA
Assumption1: Your dependentvariable should be measuredat the interval or ratiolevel (i.e., theyare continuous). Examples ofvariables that meet thiscriterion include revision time(measured in hours),intelligence (measured using IQscore), exam performance(measured from 0 to 100),weight (measured in kg), and
Assumption 2: Your independentvariable should consist of two or morecategorical, independent groups.Typically, a one-way ANOVA is usedwhen you have three ormore categorical, independent groups.Example independent variables thatmeet this criterion include ethnicity(e.g., 3 groups: Caucasian, AfricanAmerican and Hispanic), profession(e.g., 5 groups: surgeon, doctor, nurse,dentist, therapist), and so forth.
Assumption 3: You should haveindependence of observations,which means that there is norelationship between theobservations in each group orbetween the groups themselves.For example, there must bedifferent participants in eachgroup with no participant being inmore than one group.
Assumption 4: Your dependentvariable should be approximatelynormally distributed for eachcategory of the independent variable.We talk about the one-way ANOVArequiring only approximately normaldata because it is quite "robust" toviolations of normality, meaning thatassumption can be a little violated andstill provide valid results. You can testfor normality using the Shapiro-Wilktest of normality, which is easily testedfor using SPSS.
Assumption 5: There needs to behomogeneity of variances. You cantest this assumption in SPSS usingLevenes test for homogeneity ofvariances.
Click Analyze > Compare Means > One-WayANOVA... on the top menu as shown below.
The chi-square test for independence, also called Pearsons chi-square test or the chi-square test of association, is used todiscover if there is a relationship between two categoricalvariables.Assumption #1: Your two variables should be measured atan ordinal or nominal level (i.e., categorical data).Assumption #2: Your two variable should consist of two ormore categorical, independent groups. Example independentvariables that meet this criterion include gender (2 groups:Males and Females), ethnicity (e.g., 3 groups: Caucasian,African American and Hispanic), physical activity level (e.g., 4groups: sedentary, low, moderate and high), profession (e.g., 5groups: surgeon, doctor, nurse, dentist, therapist), and so forth.
One Sample t-testIndependent Samplet-testPaired Sample t-test
*A one sample t-test is used when you want to know if there is asignificant difference between a sample mean and a test value. Thetest value can be the known mean from a population or some othervalue used to compare the sample mean against.*An independent-samples t-test is used when you want to comparethe mean scores on some continuous variable for two differentgroups of subjects.*The Paired Samples t test compares the means of two variables. Itcomputes the difference between the two variables for each case,and tests to see if the difference is significant or not.*
Some Helpful Website Links….. www.spssvideotutor.com www.statistics.laerd.com http://faculty.vassar.edu http://home.clara.net/sisa/index.htm