Before calculating a correlation coefficient or a regression equation, it is always important to examine a scatter diagram between two variables to see how well a straight line fits the data. If a straight line does not appear to fit, other curves can be used to describe the relationship (this subject is not discussed in our text).
The SPSS scatterplot in Figure 13.31 and output shown in Figure 13.32 display the relationship between education (measured in years) and television viewing (measured in hours) based on 2010 GSS data. We can hypothesize that as educational attainment increases, hours of television viewing will decrease, indicating a negative relationship between the two variables.
Interpret the results of the scatterplot, as well as the "Coefficients" and "Model Summary" output.

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Scatterplot of Hours of Television Viewing per Day by Highest Year of School Completed Figure 13.31 25 20 15 10 0 0 5 10 15 20 Highest year of school completed Linear Regression Output Specifying the Relationship Between Education and Hours Spent per Day Watching Television Figure 13.32 Coefficients Standardized Unstandardized CoefficientsCoeficients Beta (Constan。 0.130 383 16.884 HIGHEST YEAR OF SCHOOL COMPLETED 231 026 -268-8.818 a Dependent Variable: HOURS PER DAY WATCHING TV Model Summary Adjusted RStd Eror of the Estimate R SquareSquare Model R 268 071 2.553 a Predictors: (Constan). HIGHEST YEAR OF SCHOOL COMPLETED