Question

Data given is contains insurance classification, price and attributes of some cars in 1987. The aim of the study is to understand how insurance risk ratings and car attributes affect the price at which a car is sold. The variables in the data set are as follows:

1. Risk rating

-3, -2, -1, 0, 1, 2, 3.

2. Risk factor

Risky, neutral, safe

3. make

alfa-romero, audi, bmw, chevrolet, dodge, honda, isuzu, jaguar, mazda, mercedes-benz, mercury, mitsubishi, nissan, peugot, plymouth, porsche, renault, saab, subaru, toyota, volkswagen, volvo

4. fuel-type

diesel, gas.

5. aspiration

standard, turbo.

6. num-of-doors

four, two.

7. body-style

hardtop, wagon, sedan, hatchback, convertible.

8. drive-wheels

4wheel drive (4wd), forward wheel drive (fwd), rear wheel drive (rwd).

9. engine-location

front, rear.

10. wheel-base

continuous from 86.6 120.9.

11. length

continuous from 141.1 to 208.1.

12. width

continuous from 60.3 to 72.3.

13. height

continuous from 47.8 to 59.8.

14. curb-weight

continuous from 1488 to 4066.

15. engine-type

dohc, dohcv, l, ohc, ohcf, ohcv, rotor.

16. num-of-cylinders

eight, five, four, six, three, twelve, two.

17. engine-size

continuous from 61 to 326.

18. fuel-system

1bbl, 2bbl, 4bbl, idi, mfi, mpfi, spdi, spfi.

19. bore

continuous from 2.54 to 3.94.

20. stroke

continuous from 2.07 to 4.17.

21. compression-ratio

continuous from 7 to 23.

22. horsepower

continuous from 48 to 288.

23. peak-rpm

continuous from 4150 to 6600.

24. city-mpg

continuous from 13 to 49.

25. highway-mpg

continuous from 16 to 54.

26. price

continuous from 5118 to 45400.

We would like to understand how the variables interact with each other. report that includes the following:

1. Calculate and interpret 95% confidence intervals of the proportion of cars that have two doors
2. Auto world magazine published an article on car efficiency in Dec 1987. The article claimed that the average city mileage of cars in 1987 was higher than that in 1985. Test auto world's hypothesis assuming that the average city mileage in 1985 was 22 mpg.
3. Test the hypothesis that on average safe cars are more expensive than risky cars.
4. Test for the independence of the risk factor and number of doors.

Please request data set, need answers asap

Answer 1

DATA SET :

Brands	Rating	Risk factor	Fuel type	Aspiration	Number of doors	Body style	Drive wheels	Engine location	Wheel base	Length	Breadth	Height	curb weight	engine type	number of cylinders	engine size	fuel systems	Bore	Stroke	Compensatio ratio	Horse power	Peak	City mpg	Highway mpg	Price
Audi	0	Neutral	Diesel	STD	4	Hard top	4 Wheel	front	87	159	61	47	3000	rotor	2	206	spfi	2.61	2.17	8	56	4230	15	18	6000
BMW	1	Risky	Gas	Turbo	2	Sedan	Forward	front	95	165	65	57	2599	dohc	5	317	1bbl	3.65	3.65	19	100	4489	18	20	8620
Chevrolet	-2	Safe	Gas	STD	4	Wagon	reverse	front	101	201	62	51	1999	dohcv	6	322	2bbl	3.45	4.01	17	250	4695	16	19	19870
Honda	-3	Safe	Gas	Turbo	2	Hatchback	4 Wheel	rear	91	175	70	52	3000	l	8	238	4bbl	3.52	3.98	21	288	5820	14	16	24630
Mazda	-1	Safe	Diesel	Turbo	4	Hard top	Forward	front	109	205	66	59	2399	ohc	12	129	idi	2.95	2.09	13	123	6532	18	19	10567
Mercedes	2	Risky	Gas	STD	4	Convertible	reverse	front	115	142	69	48	1799	ohcf	4	76	mfi	3.78	2.61	12	145	6198	19	22	33650
Mitsubishi	-1	Safe	Diesel	Turbo	2	Convertible	4 Wheel	rear	89	195	63	50	2066	ohcv	3	82	mpfi	3.71	3.25	9	198	6245	21	23	42500
Porche	3	Risky	Gas	Turbo	4	Sedan	Forward	rear	99	181	70	56	2666	rotor	2	199	spdi	3.25	3.74	10	176	6111	22	23	28900

Step 1: 95% Confidence for number of doors :

STEP 1	Column1			Mean	3.25
				95% confindence	0.86
	Mean	3.25
	Standard Error	0.36596253		High	4.11
	Median	4		Low	2.39
	Mode	4
	Standard Deviation	1.03509834
	Sample Variance	1.07142857
	Kurtosis	-2.24
	Skewness	-0.6440612
	Range	2
	Minimum	2
	Maximum	4
	Sum	26
	Count	8
	Confidence Level(95.0%)	0.86536387

STEP 2:

	Anova: Single Factor
	SUMMARY
	Groups	Count	Sum	Average	Variance
	Column 1	8	143	17.875	7.83928571
	Column 2	8	160	20	6.28571429
	ANOVA
	Source of Variation	SS	df	MS	F	P-value	F crit
	Between Groups	18.0625	1	18.0625	2.55752212	0.13208807	4.60010994
	Within Groups	98.875	14	7.0625
	Total	116.9375	15

	STEP 3: Test hypothesis of 2 different but influencing variances
	t-Test: Two-Sample Assuming Unequal Variances
		Variable 1	Variable 2
	Mean	2.375	21842.125
	Variance	0.55357143	168653542
	Observations	8	8
	Hypothesized Mean Difference	1
	df	7
	t Stat	-4.7567991
	P(T<=t) one-tail	0.00103356
	t Critical one-tail	1.89457861
	P(T<=t) two-tail	0.00206713
	t Critical two-tail	2.36462425

STEP 4: Test hypothesis between Risk Vs number of doors

t-Test: Two-Sample Assuming Unequal Variances
	Variable 1	Variable 2
Mean	2.375	3.25
Variance	0.55357143	1.07142857
Observations	8	8
Hypothesized Mean Difference	1
df	13
t Stat	-4.1602515
P(T<=t) one-tail	0.00055979
t Critical one-tail	1.7709334
P(T<=t) two-tail	0.00111958
t Critical two-tail	2.16036866