Question

Chi-Square Test of Independence. A market analyst for an automobile company suspects there are differences in the vehicle color preferred by male and female buyers. Advertisements targeted to the different groups should take such preferences into account if they exist. The first dataset shows the "observed frequencies" of the most recent sales. This is followed by partially completed tables of expected cell frequencies and chi-square calculations. Please calculate the p-value.

	Gender of Buyer
Color	Male	Female
Silver	470	280
Black	535	285
Red	495	350

Expected cell frequency (E) for each cell probability
	Gender of Buyer
Color	Male	Female	Row Total
Silver	465.84	284.16	750
Black		310.68
Red	524.84		845
Column Total		915	2,415

  

Calculation of chi-square statistic
	Gender of Buyer
Color	Male	Female
Silver	0.04	0.06
Black		2.12
Red	1.70

		0.0000
		0.0184
		8.0002
		0.0251
		None of the above

Answer 1

Expected frequencies:

	Male	Female	Row Total
Silver	465.84	284.16	750
Black	820-310.68=509.32	310.68	2415-750-845=820
Red	524.84	845-524.84=320.16	845
Column Total	2415-915=1500	915	2415

Chi square statistic =

Thus, Chi square statistic (black, male) =

Chi square statistic (red, female) =

So,Chi square statistic = 0.04+0.06+2.78+2.12+1.70+1.29 = 7.99

Thus, p-value =

Hence 2nd option is the correct option.