Table 5

Regression Models to Explain Double Jeopardy in Long Tail with Log Average Time Spent as the Dependent Variable

Statistic	Model 1		Model 2		Model 3		Model 4
Statistic	β	T	β	T	β	T	β	T
Unique (log)	.262**	33.07	.264**	33.27	.266**	33.49	.083**	14.23
News			−.084**	−9.82	−.084**	−9.87	−.115**	−18.60
Lifestyle			−.125**	−11.28	−.125**	−11.28	−.084**	−10.43
Sports			.167**	8.61	.166**	8.57	−.035**	−2.47
Months					^†	^†	^†	^†
Visits (root)							.536**	147.14
Control
Intercept	−.052*	−1.98	−.040	−1.51	−.058	−2.05	−.309*	−14.83
Adjusted R²	.043		.055		.056		.503

Note. N = 24,000. The dependent variable is the logarithm of average total minutes in millions.
↵† After adding monthly data as an independent variable, the author found that there were no significant effects on beta values.
*p < .05. **p < .01.