Question

find the regression? equation, letting the first variable be the predictor? (x) variable. Using the listed? lemon/crash data, where lemon imports are in metric tons and the fatality rates are per? 100,000 people, find the best predicted crash fatality rate for a year in which there are 525 metric tons of lemon imports. Is the prediction? worthwhile? Lemon Imports 226 270 354 483 544 Crash Fatality Rate 16 15.7 15.5 15.4 15 Find the equation of the regression line y = _ +? _x ?(Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.

The best predicted crash fatality rate for a year in which there are 525 metric tons of lemon imports is 15.1 fatalities per? 100,000 population.

?(Round to one decimal place as? needed.)

Is the prediction? worthwhile?

A.

Since all of the requirements for finding the equation of the regression line are? met, the prediction is worthwhile.

B.

Since the sample size is? small, the prediction is not appropriate.

C.

Since common sense suggests there should not be much of a relationship between the two? variables, the prediction does not make much sense.

D.

Since there appears to be an? outlier, the prediction is not appropriate.

Answer 1

Result:

find the regression? equation, letting the first variable be the predictor? (x) variable. Using the listed? lemon/crash data, where lemon imports are in metric tons and the fatality rates are per? 100,000 people, find the best predicted crash fatality rate for a year in which there are 525 metric tons of lemon imports. Is the prediction? worthwhile?

LemonImports 226 270 354 483 544

CrashFatalityRate 16 15.7 15.5 15.4 15

Find the equation of the regression line

y = 16.490+( -0.002583)x

?(Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.

The best predicted crash fatality rate for a year in which there are 525 metric tons of lemon imports is 15.1 fatalities per? 100,000 population.

?(Round to one decimal place as? needed.)Is the prediction? worthwhile?

Answer: A.Since all of the requirements for finding the equation of the regression line are met, the prediction is worthwhile.

B.Since the sample size is? small, the prediction is not appropriate.

C.Since common sense suggests there should not be much of a relationship between the two? variables, the prediction does not make much sense.

D.Since there appears to be an? outlier, the prediction is not appropriate.

Regression Analysis
	r²	0.899	n	5
	r	-0.948	k	1
	Std. Error	0.136	Dep. Var.	CrashFatalityRate
ANOVA table
Source	SS	df	MS	F	p-value
Regression	0.49288556	1	0.49288556	26.83	.0140
Residual	0.05511444	3	0.01837148
Total	0.54800000	4
Regression output					confidence interval
variables	coefficients	std. error	t (df=3)	p-value	95% lower	95% upper
Intercept	16.489552	0.1968	83.808	3.74E-06	15.8634	17.1157
LemonImports	-0.002583	0.00049863	-5.180	.0140	-0.0042	-0.0010
Predicted values for: CrashFatalityRate
		95% Confidence Interval		95% Prediction Interval
LemonImports	Predicted	lower	upper	lower	upper	Leverage
525	15.1336	14.8277	15.4395	14.6048	15.6624	0.503