Evaluation of Factors Affecting E-Bike Involved Crash and E-Bike License Plate Use in China Using a Bivariate Probit Model

Table 2

Descriptive statistics for demographic information.

Variable	Descriptive	Frequency	Percentage (%)
Individual characteristics
Gender	Male	438	50.8
	Female	424	49.2
Age group	Young (<30)	463	53.7
	Middle-aged (30–60)	286	33.2
	Older (>60)	113	13.1
Education level	High (postgraduate and higher)	141	16.4
	Middle (junior college or undergraduate)	343	39.8
	Middle-low (high school and junior middle school)	294	34.1
	Low (junior middle school and lower)	84	9.7
Occupation	Student	105	12.2
	Employee in enterprise/company	244	28.3
	Officer	119	13.8
	Self-employed	143	16.6
	Freelance	128	14.8
	Retired	76	8.8
	Others	47	5.5
Holding automobile driver license	Yes	552	64.0
	No	310	36.0
Household characteristics
Number of e-bikes in household	1	506	58.7
	>1	356	41.3
Car in household	Yes	256	29.7
	No	606	70.3
Type of e-bike	Scooter style	401	46.5
	Bicycle style	461	53.5