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  For statisticians and analysts in fields ranging from education and health care to business and public policy, SPSS 16 is a valuable tool for analyzing large sets of data and answering critical research questions. SPSS, a software company acquired by IBM, released SPSS 16.0 in 2008. Like most spreadsheets and statistical software, SPSS 16.0 can calculate basic descriptive statistics, such as frequency distributions, means, medians and standard deviations. Its Tables function enables you to display summarized data in rows and columns. For users with statistical knowledge and whose research questions require more rigorous analysis, SPSS' capabilities include a range of complex statistical procedures.
  
  

Linear Regression

• A favorite statistical method among economists and other social science researchers, linear regression analyzes the change in an effect, or dependent variable, resulting from changes in one or more predictors, or independent variables. An economist, for example, may study the extent to which additional years of education or work experience changes the average salary received by professionals in a particular industry. SPSS 16 offers the regression option in its menu of analytical procedures. To conduct a regression analysis, click the Analyze pull-down menu at the top of an SPSS spreadsheet, then select "Regression." This opens a regression window that allows you to enter the dependent and independent variables you want analyzed. SPSS can display results in tabular form and with graphics.
  
  

Logistic and Probit Regression

• Logistic and probit regression procedures involve dependent variables or effects that are binary. Whether a person graduated high school or whether someone is male or female are examples of binary dependent variables. The Regression option under the "Analyze" menu in SPSS 16 enables you to conduct both types of regression analysis. Choosing the regression option under the Analyze menu will give a range of regression options, including logistic and probit, as well as linear regression.
  
  

Factor Analysis

• Popular in survey and marketing research, factor analysis reduces a large set of data to identify underlying factors and how they influence a set of related measures. This procedure is beyond the scope of many spreadsheet programs, such as Microsoft Excel. SPSS 16.0, however, enables you to conduct factor analysis by clicking the "Analyze" pull-down menu and selecting "Data Reduction," then choosing "Factor Analysis." This opens a window that allows you to select the measures to analyze.