• A biologist is studying the levels of heavy metal contaminants among a population of the South Nakaratuan Chubby Bat. The biologist is interested in constructing a simple linear regression model to investigate the relationship between weight of an animal and the level of heavy metal contamination. In the proposed regression model the level of contaminant is the response variable and weight is the explanatory variable. The contaminant level is measured in parts per billion (ppb) and weight in grams. The SPSS output is given below. Use the output to answer the following questions.

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.921a	.848	.839	13.82229
a. Predictors: (Constant), weight
ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	18143	1	18143	94.96	.000b
Residual	3247.94781	17	191.05575
Total	21391	18
a. Dependent Variable: contaminant
b. Predictors: (Constant), weight

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	-71.63611	28.17794		-2.54	.021
weight	2.18277	0.22399	.921	9.74	.000
a. Dependent Variable: contaminant

What percent of variation in the values of contaminant level that is explained by the linear regression model between contaminant level and weight?What is the correlation between contaminant level and weight?What is the predicted contaminant level for an animal weighted 150 grams?One of the animals in this analysis had a weight of 145 grams and contaminant level of 222 ppb. What is the residual for this observation?What is least squares regression line?What is the average change in contaminant level when the weight of an animal is increased by 1 gram?Construct a 99% confidence interval for the regression slope.The biologist wants to determine whether there is a positive linear association between contaminant level and weight of an animal. Write down the appropriate hypotheses, value of test statistic, degrees of freedom of the test statistic, p-value, and the conclusion.1.A biologist is studying the levels of heavymetal contaminants among a population of the South Nakaratuan Chubby Bat. Thebiologist is interested in constructing a simple linear regression model toinvestigate the relationship between weight of an animal and the level of heavymetal contamination. In the proposed regression model the level of contaminantis the response variable and weight is the explanatory variable. Thecontaminant level is measured in parts per billion (ppb) and weight in grams.The SPSS output is given below. Use the output to answer the followingquestions.

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.921a	.848	.839	13.82229
a. Predictors: (Constant), weight
ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	18143	1	18143	94.96	.000b
Residual	3247.94781	17	191.05575
Total	21391	18
a. Dependent Variable: contaminant
b. Predictors: (Constant), weight

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	-71.63611	28.17794		-2.54	.021
weight	2.18277	0.22399	.921	9.74	.000
a. Dependent Variable: contaminant

(1) Whatpercent of variation in the values of contaminant level that is explained bythe linear regression model between contaminant level and weight?

(2)What is the correlation between contaminantlevel and weight?

(3)What is the predicted contaminant level for ananimal weighted 150 grams?

(4) One of theanimals in this analysis had a weight of 145 grams and contaminant level of 222ppb. What is the residual for this observation?

(5) What isleast squares regression line?

(6) What isthe average change in contaminant level when the weight of an animal isincreased by 1 gram?

(7) Constructa 99% confidence interval for the regression slope.

(8) Thebiologist wants to determine whether there is a positive linear associationbetween contaminant level and weight of an animal. Write down the appropriatehypotheses, value of test statistic, degrees of freedom of the test statistic,p-value, and the conclusion.