Statistic 7

Valerie_data_7.xlsx

Sheet2

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.865508314
R Square	0.7491046416
Adjusted R Square	0.7177427218
Standard Error	2.2547210913
Observations	10
ANOVA
	df	SS	MS	F	Significance F
Regression	1	121.4298624024	121.4298624024	23.8858031126	0.0012130798	(P-value) < alpha - Yes, this is a significant predictor
Residual	8	40.6701375976	5.0837671997
Total	9	162.1
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	1.607288955	4.1725703027	0.3852035648	0.7101262342	-8.0146754175	11.2292533275	-8.0146754175	11.2292533275
MPG Highway	0.6719970249	0.1374983309	4.887310417	0.0012130798	0.3549253053	0.9890687445	0.3549253053	0.9890687445
RESIDUAL OUTPUT
Observation	Predicted MPG (city)	Residuals	Standard Residuals
1	20.4232056527	4.5767943473	2.1530039779
2	17.0632205281	-1.0632205281	-0.5001575016
3	18.4072145779	-1.4072145779	-0.6619783093
4	17.0632205281	0.9367794719	0.440677421
5	24.4551878022	-0.4551878022	-0.2141282903
6	27.8151729267	2.1848270733	1.0277808052
7	19.7512086277	0.2487913723	0.1170358057
8	24.4551878022	-0.4551878022	-0.2141282903
9	24.4551878022	-2.4551878022	-1.154963213
10	23.1111937523	-2.1111937523	-0.9931424053

Vehicle type/class	Year	Make	Model	Price	MPG (city)	MPG Highway	Odometer/Miles
Compact SUV	2021	Ford	Bronco Sport	$ 35,875	25	28	0
Pickup	2020	Ram	1500 Express	$ 39,399	16	23	7
Compact SUV	2018	Jeep	Wrangler Rubicon	$ 34,000	17	25	35855
Pickup	2016	Toyota	Tacoma	$ 30,000	18	23	42061
Sedan	2018	Ford	Focus Titanium	$ 12,649	24	34	32792
Sedan	2019	Volkswagen	Jetta S	$ 13,900	30	39	5990
Crossover	2017	Ford	Escape SE	$ 15,699	20	27	7313
Sedan	2017	Mercedes-Benz	C300 4Matic	$ 26,580	24	34	34028
Coupe	2016	BMW	428i Gran Coupe xDrive	$ 24,490	22	34	44336
Sedan	2019	Volvo	S60 T6 Momentum AWD	$ 25,991	21	32	19736
					Correlations	0.8655	Positive Correlation
					R2	74.91%	Strongest Correlation = 100%, 74.91% is strong enough that it will still give us a good indication and we can further interpret the data.
					Significance F	0.0012130798	(P-value) < alpha - Yes, MPG Highway is a significant predictor of MPG City.
				Coefficients	Intercept	1.6073
					MPG Highway	0.6720
					Regression Equation	MPG City = .6720 (MPG Highway) + 1.6073
					y^ = β1x + β0	MPG City = .6720 (MPG Hwy) + 1.6073
					y intercept =	MPG City = .6720 (0) + 1.6073
						MPG City = 1.6073
					Slope	As the MPG Highway increases by 1, then the MPG City will increase by .6720.
					Regression	MPG City = .6720 (50) + 1.6073	When the MPG Hwy is 50 miles per gallon, then the
						MPG City = 33.6 + 1.6073	MPG city is expected to be 35.21 miles per gallon.
						MPG City = 35.21