Understanding the Usage Patterns of Bicycle-Sharing Systems to Predict Users’ Demand: A Case Study in Wenzhou, China

Table 1

Bivariate correlate and partial correlate results.

			Temperature	Wind speed	Rainfall	Working/nonworking day
Bivariate correlate	Daily total trips	Correlation	0.332	0.126	−0.607	−0.504
		Significance (2-tailed)	0.000	0.021	0.000	0.000
		df	335	335	335	335
Partial correlate	Daily total trips	Correlation	0.354	0.161	−0.625	−0.518
		Significance (2-tailed)	0.000	0.003	0.000	0.000
		df	330	330	330	330

Correlation is significant at the 0.01 level (2-tailed). Correlation is significant at the 0.05 level (2-tailed).