Predicting Daily Television Viewing of Senior Citizens Using Education, Age and Marital Status

Paul R. Yarnold

Optimal Data Analysis, LLC

Daily television viewing (hours, 6-minute increments), marital status (0=not married; 1=married), age and education (years, integers) data were obtained for a randomly-selected sample of 25 senior citizens. Training analysis predicting viewing (dependent variable) as a linear function of the other (independent) measures by multiple regression analysis identified a statistically significant omnibus effect: F(3,21)=11.7, p<0.0001, R-squared=0.626. Partial F (variable entered last) statistics indicated that marital status [F(1,21)=13.9, p<0.0008] and education [F(1,21)=9.2, p<0.0062] had statistically reliable negative relationships with viewing hours. This model accounted for 5/8 of the variance in television viewing time, however it was unable to make statistically reliable point predictions of viewing times: ESS=7.1, D=194.9, ns. The globally-optimal (GO) novometric model predicting viewing times was: if education<=13 years, then predict viewing 0.7 hours. Training performance (stable in jackknife analysis) was very strong: ESS=90.1, D=0.20, p<0.0001. The model correctly classified 3 of 3 observations having 0.7 or fewer viewing hours, and 20 of 22 (90.1%) with 0.8 or more daily viewing hours.

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