spss statistics

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SPSS Statistics Instructor: Sergio Robleto Ramírez

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Explaining basics for using SPSS

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Page 1: SPSS Statistics

SPSS StatisticsInstructor: Sergio Robleto Ramírez

Page 2: SPSS Statistics

About Spss SPSS Inc., an IBM Company, is a leading global provider of predictive analytic software and solutions. The company’s complete portfolio of products — data collection, statistics, modeling and deployment — captures people’s attitudes and opinions, predicts outcomes of future customer interactions, and then acts on these insights by embedding analytics into business processes.

Page 3: SPSS Statistics

Variable levels You can specify the level of measurement as scale (numeric data on an interval or ratio scale), ordinal, or nominal. Nominal and ordinal data can be either string (alphanumeric) or numeric.

Nominal: A variable can be treated as nominal when its values represent categories with no intrinsic ranking (for example, the department of the company in which an employee works).Examples of nominal variables include region, zip code, and religious affiliation.

Ordinal: A variable can be treated as ordinal when its values represent categories with some intrinsic ranking (for example, levels of service satisfaction from highly dissatisfied to highly satisfied). Examples of ordinal variables include attitude scores representing degree of satisfaction or confidence and preference rating scores.

Scale: A variable can be treated as scale (continuous) when its values represent ordered categories with a meaningful metric, so that distance comparisons between values are appropriate. Examples of scale variables include age in years and income in thousands of dollars.

Page 4: SPSS Statistics

Variable levels

Page 5: SPSS Statistics

Variable Type dialog box Numeric. A variable whose values are numbers. Values are displayed in standard numeric format.

Comma. A numeric variable whose values are displayed with commas delimiting every three places and displayed with the period as a decimal delimiter.

Dot. A numeric variable whose values are displayed with periods delimiting every three places and with the comma as a decimal delimiter.

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.

Page 6: SPSS Statistics

Variable Type dialog box 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.

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.

Page 7: SPSS Statistics

Value Labels You can assign descriptive value labels for each value of a variable. This process is particularly useful if your data file uses numeric codes to represent non-numeric categories (for example, codes of 1 and 2 for male and female).

To specify value labels

- Click the button in the Values cell for the variable that you want to define.

- For each value, enter the value and a label.

- Click Add to enter the value label.

- Click OK