1. What is the response variable? morning high tide levels + 2. What is the regression line equation? (Round each value to the nearest hundredth, if necessary.) y = 3. We can expect the PM high tide on January 4 to be approximately feet. (Round to the nearest tenth, if necessary.) This is an example of interpolation + 4. The correlation coefficient is (round to the nearest hundredth) .This value means that there is moderate : no correlation between the AM and PM tide levels. 5. Change the regression model from linear to test and see if an exponential or a quadratic function is a better fit for this data set. It appears that the quadratic ÷ function is a better fit. 6. Use the new equation to estimate the value of the PM high time on January 4. The estimated PM high tide is (Round to the nearest tenth, if necessary.)

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Can you please answer ALL parts of it??

Day AM High (in feet), x PM High (in feet), y
5.6
4.8
5.5
4.8
3
5.4
4.9
4
5.2
5.0
5.1
5.2
5.0
7
5.4
4.9
8
5.7
5.0
9
6.0
5.1
10
6.3
5.3
11
6.4
5.4
12
6.5
5.4
13
6.4
5.4
14
6.2
5.3
2.
Transcribed Image Text:Day AM High (in feet), x PM High (in feet), y 5.6 4.8 5.5 4.8 3 5.4 4.9 4 5.2 5.0 5.1 5.2 5.0 7 5.4 4.9 8 5.7 5.0 9 6.0 5.1 10 6.3 5.3 11 6.4 5.4 12 6.5 5.4 13 6.4 5.4 14 6.2 5.3 2.
1. What is the response variable? morning high tide levels +
2. What is the regression line equation? (Round each value to the
nearest hundredth, if necessary.) y =
3. We can expect the PM high tide on January 4 to be approximately
feet. (Round to the nearest tenth, if necessary.) This is an
example of interpolation +
4. The correlation coefficient is (round to the nearest hundredth)
. This
value means that there is moderate +
no
correlation between the AM and PM tide levels.
5. Change the regression model from linear to test and see if an
exponential or a quadratic function is a better fit for this data set.
It appears that the quadratic : function is a better fit.
6. Use the new equation to estimate the value of the PM high time
on January 4. The estimated PM high tide is
(Round to
the nearest tenth, if necessary.)
Transcribed Image Text:1. What is the response variable? morning high tide levels + 2. What is the regression line equation? (Round each value to the nearest hundredth, if necessary.) y = 3. We can expect the PM high tide on January 4 to be approximately feet. (Round to the nearest tenth, if necessary.) This is an example of interpolation + 4. The correlation coefficient is (round to the nearest hundredth) . This value means that there is moderate + no correlation between the AM and PM tide levels. 5. Change the regression model from linear to test and see if an exponential or a quadratic function is a better fit for this data set. It appears that the quadratic : function is a better fit. 6. Use the new equation to estimate the value of the PM high time on January 4. The estimated PM high tide is (Round to the nearest tenth, if necessary.)
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