Inferential Statistics and Findings

Running head: BUSINESS RESEARCH PROJECT PART 1

Business Research Project Part 1: Formulation of the Research Problem

With the rising gas prices, consumers tend to conduct research when shopping for a new vehicle. Team B has been tasked with conducting research for Automotive Trends. The team is looking into the correlation between vehicles weight and highway fuel economy. The purpose of this paper is to review the dependent and independent variables for these and to come up with a hypothesis. Team B will generate a research question to get this started.

Research Question

When looking at the research question, Team B has decided to look at the correlation between the weight of the vehicle and the highway miles per gallon. The following is the research question:

Is there a direct correlation between vehicles weight and the highway fuel mileage?

To answer this, Team B had to determine the variables that would be reviewing in researching. The first variable is the independent variable. In this scenario, the independent variable would be the highway fuel mileage. The second variable is the dependent variable. With this scenario, the dependent variable is the vehicles weight. The weight of the vehicle will remain constant while the highway fuel mileage can vary based on driving conditions.

Hypothesis

Team B generated a hypothesis for the research question. The hypothesis is a statistical

inference using data (McClave, Benson, & Sincich, 2011). The hypothesis Team B generated is

as follows:

Ho: There is a direct correlation between vehicle weight (DV) and highway fuel mileage (IV).
H1: There is no direct correlation between vehicle weight (DV) and highway fuel mileage (IV).

Data

Team B investigated 32 different vehicles from 26 different manufacturers. The team collected the weights of the vehicles; overall length; braking distance; number of cylinders; displacement; city and highway miles per gallon; and greenhouse gases.

The results for the vehicles are below as follows:

Car	Weight	Length	Braking	Cylinders	Displacement	City	Highway	GHG
Acura RL	4035	194	131		3.5	18	26	8.7
Acura TSX	3315	183	136		2.4	22	31	7.2
Audi A6	4115	194	129		3.2	21	29	7.7
BMW 525i	3650	191	127		3.0	21	29	7.7
Buick LaCrosse	3565	198	146		3.8	20	30	7.9
Cadillac STS	4030	196	146		3.6	18	27	8.7
Chevrolet Impala	3710	200	155		3.9	19	27	8.2
Chevrolet Malibu	3135	188	139		2.2	24	32	6.8
Chrysler 300	4105	197	133		5.7	17	25	9.3
Dodge Charger	4170	200	131		5.7	17	25	9.3
Dodge Stratus	3190	191	131		2.4	22	30	7.4
Ford Crown Victoria	4180	212	140		4.6	17	25	9.3
Ford Focus	2760	168	137		2.0	26	32	6.5
Honda Accord	3195	190	144		2.4	24	34	6.6
Hyundai Elantra	2980	177	133		2.0	24	32	6.7
Infiniti M35	4095	193	122		3.5	18	25	9.0
Jaguar XJ8	3860	200	133		4.2	18	27	8.6
Kia Amanti	4020	196	143		3.5	17	25	9.3
Kia Spectra	2875	176	144		2.0	25	34	6.5
Lexus GS300	3915	190	133		3.0	22	30	7.4
Lexus LS	4205	197	134		4.3	18	25	8.7
Lincoln Town Car	4415	215	143		4.6	17	25	9.3
Mazda 3	3060	177	129		2.3	26	32	6.5
Mercedes-Benz E	3745	190	128		3.2	27	37	7.0
Mercury Grand Marquis	4180	212	140		4.6	17	25	9.3
Nissan Altima	3235	192	144		2.5	23	29	7.1
Pontiac G6	3475	189	146		3.5	22	32	7.2
Saturn Ion	2865	185	130		2.2	24	32	6.7
Toyota Avalon	3600	197	139		3.5	22	31	7.2
Toyota Corolla	2595	178	140		1.8	30	38	5.5
Volkswagon Passat	3465	188	135		2.0	22	31	7.3
Volvo S80	3630	190	136		2.9	20	27	8.2
Sum	115370	6144	4377	180	104.0	678	939	248.8000
Mean	3605.31	192.00	136.78	5.63	3.25	21.19	29.34	7.78
Median	3640.0	191.5	136.0	6.0	3.2	21.5	29.5	7.6

References

McClave, J. T., Benson, P. G., & Sincich, T. (2011). Statistics for Business and Economics (11th

ed.). Boston, MA: Prentice Hall.