Please help answer the following.An explanation as to how you got the answers you did would be great. DataSet: {(−3, 4), (−2, 3), (−1, 3), (0, 7), (1, 5), (2, 6), (3, 1)}1. The regression line is: y =2. Based on the regression line, we would expect the value ofresponse variable to bewhen the explanatoryvariable is 0.3. For each increase of 1 in of the explanatory variable, wecan expect a(n)in the responsevariable.4. If x =-3.5, the y=Xof5. The correlation coefficient is r =nearest hundredth.)This is an example of(Round to the Data Set:{(1,4), (2, 6), (3,8), (4, 10), (5, 12), (6, 14), (7, 16)}1. The regression line is: y =+2. Based on the regression line, we would expect the value of0when the explanatoryresponse variable to bevariable is 0.3. For each increase of 1 in of the explanatory variable, wecan expect a(n)in the responsevariable.4. If x= 3.5, the y=XofThis is an example of5. The correlation coefficient is r =nearest hundredth.)(Round to the

Data set: This can be expressed as follows: xy142638410512614716NOTE: Hi there! Thanks for posting…

Data Set: {(1,4), (2,6), (3, 8), (4, 10), (5, 12), (6, 14), (7, 16)} 1. The regression line is: y = +C 2. Based on the regression line, we would expect the value of response variable to be when the explanatory variable is 0. 3. For each increase of 1 in of the explanatory variable, we can expect a(n) in the response variable. 4. If x= 3.5, the y X of This is an example of 5. The correlation coefficient is r = nearest hundredth.) (Round to the

Data Set: {(1,4), (2,6), (3, 8), (4, 10), (5, 12), (6, 14), (7, 16)} 1. The regression line is: y = +C 2. Based on the regression line, we would expect the value of response variable to be when the explanatory variable is 0. 3. For each increase of 1 in of the explanatory variable, we can expect a(n) in the response variable. 4. If x= 3.5, the y X of This is an example of 5. The correlation coefficient is r = nearest hundredth.) (Round to the

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter3: Straight Lines And Linear Functions

Section3.CR: Chapter Review Exercises

Problem 15CR: Life Expectancy The following table shows the average life expectancy, in years, of a child born in...

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Question

Please help answer the following.An explanation as to how you got the answers you did would be great.

Data
Set: {(−3, 4), (−2, 3), (−1, 3), (0, 7), (1, 5), (2, 6), (3, 1)}
1. The regression line is: y =
2. Based on the regression line, we would expect the value of
response variable to be
when the explanatory
variable is 0.
3. For each increase of 1 in of the explanatory variable, we
can expect a(n)
in the response
variable.
4. If x =
-3.5, the y
=
X
of
5. The correlation coefficient is r =
nearest hundredth.)
This is an example of
(Round to the

Data Set:
{(1,4), (2, 6), (3,8), (4, 10), (5, 12), (6, 14), (7, 16)}
1. The regression line is: y =
+
2. Based on the regression line, we would expect the value of
0
when the explanatory
response variable to be
variable is 0.
3. For each increase of 1 in of the explanatory variable, we
can expect a(n)
in the response
variable.
4. If x= 3.5, the y
=
X
of
This is an example of
5. The correlation coefficient is r =
nearest hundredth.)
(Round to the

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