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Overview: SPSS
Rebecca Filipowicz, MPH, MS, CHES
Statistical Packages
 Data Entry
 Data Manipulation
 Data Analysis (Descriptive,Inferential)
 Graphs
3 SPSS File Types/Windows
 .SAV – data file/Data Editor
 .SPO – output file/Output Viewer
 .SPS – syntax file/Syntax Editor
Opening a Dataset
Data can be entered directly or a file containing
data can be open (can be in a variety of
formats)
Data View (contains the data)
Variable View (contains information about the
variables)
Data Editor
 Menu commands
 File: open, reads, saves, exits
 Edit: copy, paste, find
 View: control the way screen appears
 Data: define, go to data, sort cases, merge
file, select cases
 Transform: manipulates data (compute and
recode)
Data Editor
 Menu Commands
 Analyze: data analysis
 Graphs: create graphs
 Utilities: list variables
 Window: position and format windows
 Help: Tutorial, index
Creating a new variable
 Name
 Type
 Width
 Decimals
 Label
 Values (used in
output display)
 Missing values
(used mostly for
NA or refused -
will not include in
analysis if
designated)
 Column format
 Alignment
 Measurement
Variable Type
 Numeric
 Comma
 Dot
 Scientific notation
 Date
 Dollar
 Custom Currency
 String
Labels
 The text that describes the response
categories
1=American Indian
2=Asian
3=Black
4=Hispanic
5=Native Hawaiian
6=White
Create Sample Survey
 Entering data
 Click in the cell
 Type in the response code
 Press right arrow
 Missing
 Skip the question
 Press right arrow to go to the next variable
Editing and Finding Data
 Review case’s responses
 Make a change to case’s responses
 Searching for cases that meet a certain
criteria
 Finding Variables: Go To
 Finding Cases: Go To
 Sorting variables/cases
Opening data
 A lot of formats you can import from and
export to (will do some of this in the closing
on campus session)
Working with Data
 Know your questions
 Know your codebook
 Question
 Name of variable
 Level of measurement
 Response type (numeric, date, text, etc.)
 Response categories
 Text labels
Analyze Data
 Basic
 Descriptive Statistics
 Frequencies
 Descriptives (mean)
 Cross tabs
 Reports
 Case summaries
Outputs
 Output Viewer
 Left frame – outline of objects in window
 Contains syntax at top of figure
 Figures, Titles, Dataset, Notes
 Deleting
 Editing
 Exporting
Other Analyses
 Correlations
 T-test
 Logistic and linear regression
 ANOVA and MANOVA and MANCOVA
Selecting Cases
 If condition satisfies
 New data set
 Filter only
Data manipulation
 Creating Variables
 Compute
 New variable
 Recode
 Old variables to new/same variables
Syntax
 Used for saving a log of what you have done
to to re-run what you have done at a later
date.
 Can type directly into syntax file (must know
language) or can paste from commands

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Overview spss instructor

  • 2. Statistical Packages  Data Entry  Data Manipulation  Data Analysis (Descriptive,Inferential)  Graphs
  • 3. 3 SPSS File Types/Windows  .SAV – data file/Data Editor  .SPO – output file/Output Viewer  .SPS – syntax file/Syntax Editor
  • 4. Opening a Dataset Data can be entered directly or a file containing data can be open (can be in a variety of formats) Data View (contains the data) Variable View (contains information about the variables)
  • 5. Data Editor  Menu commands  File: open, reads, saves, exits  Edit: copy, paste, find  View: control the way screen appears  Data: define, go to data, sort cases, merge file, select cases  Transform: manipulates data (compute and recode)
  • 6. Data Editor  Menu Commands  Analyze: data analysis  Graphs: create graphs  Utilities: list variables  Window: position and format windows  Help: Tutorial, index
  • 7. Creating a new variable  Name  Type  Width  Decimals  Label  Values (used in output display)  Missing values (used mostly for NA or refused - will not include in analysis if designated)  Column format  Alignment  Measurement
  • 8. Variable Type  Numeric  Comma  Dot  Scientific notation  Date  Dollar  Custom Currency  String
  • 9. Labels  The text that describes the response categories 1=American Indian 2=Asian 3=Black 4=Hispanic 5=Native Hawaiian 6=White
  • 10. Create Sample Survey  Entering data  Click in the cell  Type in the response code  Press right arrow  Missing  Skip the question  Press right arrow to go to the next variable
  • 11. Editing and Finding Data  Review case’s responses  Make a change to case’s responses  Searching for cases that meet a certain criteria  Finding Variables: Go To  Finding Cases: Go To  Sorting variables/cases
  • 12. Opening data  A lot of formats you can import from and export to (will do some of this in the closing on campus session)
  • 13. Working with Data  Know your questions  Know your codebook  Question  Name of variable  Level of measurement  Response type (numeric, date, text, etc.)  Response categories  Text labels
  • 14. Analyze Data  Basic  Descriptive Statistics  Frequencies  Descriptives (mean)  Cross tabs  Reports  Case summaries
  • 15. Outputs  Output Viewer  Left frame – outline of objects in window  Contains syntax at top of figure  Figures, Titles, Dataset, Notes  Deleting  Editing  Exporting
  • 16. Other Analyses  Correlations  T-test  Logistic and linear regression  ANOVA and MANOVA and MANCOVA
  • 17. Selecting Cases  If condition satisfies  New data set  Filter only
  • 18. Data manipulation  Creating Variables  Compute  New variable  Recode  Old variables to new/same variables
  • 19. Syntax  Used for saving a log of what you have done to to re-run what you have done at a later date.  Can type directly into syntax file (must know language) or can paste from commands

Editor's Notes

  1. Variable type Variable Type specifies the data type for each variable. By default, all new variables are assumed to be numeric. You can use Variable Type to change the data type. The contents of the Variable Type dialog box depend on the selected data type. For some data types, there are text boxes for width and number of decimals; for other data types, you can simply select a format from a scrollable list of examples. The available data types are as follows: Numeric. A variable whose values are numbers. Values are displayed in standard numeric format. The Data Editor accepts numeric values in standard format or in scientific notation. Comma. A numeric variable whose values are displayed with commas delimiting every three places and displayed with the period as a decimal delimiter. The Data Editor accepts numeric values for comma variables with or without commas or in scientific notation. Values cannot contain commas to the right of the decimal indicator. Dot. A numeric variable whose values are displayed with periods delimiting every three places and with the comma as a decimal delimiter. The Data Editor accepts numeric values for dot variables with or without periods or in scientific notation. Values cannot contain periods to the right of the decimal indicator. Scientific notation. A numeric variable whose values are displayed with an embedded E and a signed power-of-10 exponent. The Data Editor accepts numeric values for such variables with or without an exponent. The exponent can be preceded by E or D with an optional sign or by the sign alone--for example, 123, 1.23E2, 1.23D2, 1.23E+2, and 1.23+2. Date. A numeric variable whose values are displayed in one of several calendar-date or clock-time formats. Select a format from the list. You can enter dates with slashes, hyphens, periods, commas, or blank spaces as delimiters. The century range for two-digit year values is determined by your Options settings (from the Edit menu, choose Options, and then click the Data tab). Dollar. A numeric variable displayed with a leading dollar sign ($), commas delimiting every three places, and a period as the decimal delimiter. You can enter data values with or without the leading dollar sign. Custom currency. A numeric variable whose values are displayed in one of the custom currency formats that you have defined on the Currency tab of the Options dialog box. Defined custom currency characters cannot be used in data entry but are displayed in the Data Editor. String. A variable whose values are not numeric and therefore are not used in calculations. The values can contain any characters up to the defined length. Uppercase and lowercase letters are considered distinct. This type is also known as an alphanumeric variable.
  2. Handout Step Up Survey Input questions Show insert variables – insert cases
  3. Edit – Go to Variable EpiInfo Edit – Go to Case 15 Go to Data – Sort Cases by ID Data - Sort Variables (alphabetize)
  4. Open Computer and Discuss Codebook
  5. Frequency email and epi info Descriptives – mean age Cross tab – gender x wkresp
  6. Show selecting parts and copying/paste/edit/export
  7. Select – if location = “S” Select if location = “S” and gender = 1 Select – usecomp = 1 or 2 (want to look at wkresp)
  8. Compute attitude = userfriend+newthings+future+effiec+newtech Run Frequency (can then recode into labels (attlabel) Run Frequency Go back and recode (change output variable to attlabx) If age greater than 50 Run Freq of attlabx and compare to attlabel Recode age into new variable called agegrp (<=24/25-34/35-44/35-44/45-54/55-64/65+) – outputs as strings Run crosstab of agegrp to attlabel