Table 4

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

Statistic	Model 1		Model 2		Model 3		Model 4
Statistic	β	T	β	T	β	T	β	T
Unique (log)	.191^**	24.89	.203^**	26.65	.205^**	26.85	.033^**	5.85
News			−.198^**	−24.05	−.199^**	−24.10	−.227^**	−37.28
Lifestyle			−.128	−12.02	−.128^**	−12.02	−.089^**	−11.33
Sports			.058	3.14	.057	3.10	−.131^**	−9.48
Months					^†	^†	^†	^†
Visits (root)							.504^**	140.72
Control
Intercept	0.315^**	12.21	0.310^**	12.17	0.301^**	10.96	0.063^**	3.23
Adjusted R²	.025		.052		.053		.482

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