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2. Calculate the coefficients of a linear equation to predict the yield Y as a function of X. 3. Calculate the correlation coefficient for the paired data values. 4. Set up the framework for an appropriate statistical test to estab- lish if there is a correlation between the amount of the trace ele- ment and the yield. Explain how having the scatterplot referred to above and having the value of r in advance will influence the structure of your statistical test. 5. Carry out and state the conclusion of your test on the correlation. 6. Comment on how well the regression equation will perform based on the results above.

2. Calculate the coefficients of a linear equation to predict the yield Y as a function of X. 3. Calculate the correlation coefficient for the paired data values. 4. Set up the framework for an appropriate statistical test to estab- lish if there is a correlation between the amount of the trace ele- ment and the yield. Explain how having the scatterplot referred to above and having the value of r in advance will influence the structure of your statistical test. 5. Carry out and state the conclusion of your test on the correlation. 6. Comment on how well the regression equation will perform based on the results above.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Hello, I need some help answering questions 4, 5 and 6 attached. Thank you very much.

A study was carried out to determine the influence of a trace element found in soil on the yield of potato plants grown in that soil, defined as the weight of potatoes produced at the end of the season. A large field was divided up into 14 smaller sections for this experiment. For each section, the experimenter recorded the amount of the trace element found (in milligrams per metre squared) and the corresponding weight of the potatoes produced (in kilograms). This information is presented in the worksheet 'Dataset5' in the Excel document. Define X as the trace element amount and Y as the yield. 1. Draw a scatterplot of your data set. Page 5 2. Calculate the coefficients of a linear equation to predict the yield Y as a function of X. 3. Calculate the correlation coefficient for the paired data values. 4. Set up the framework for an appropriate statistical test to estab- lish if there is a correlation between the amount of the trace ele- ment and the yield. Explain how having the scatterplot referred to above and having the value of r in advance will influence the structure of your statistical test. 5. Carry out and state the conclusion of your test on the correlation. 6. Comment on how well the regression equation will perform based on the results above.
Transcribed Image Text:A study was carried out to determine the influence of a trace element found in soil on the yield of potato plants grown in that soil, defined as the weight of potatoes produced at the end of the season. A large field was divided up into 14 smaller sections for this experiment. For each section, the experimenter recorded the amount of the trace element found (in milligrams per metre squared) and the corresponding weight of the potatoes produced (in kilograms). This information is presented in the worksheet 'Dataset5' in the Excel document. Define X as the trace element amount and Y as the yield. 1. Draw a scatterplot of your data set. Page 5 2. Calculate the coefficients of a linear equation to predict the yield Y as a function of X. 3. Calculate the correlation coefficient for the paired data values. 4. Set up the framework for an appropriate statistical test to estab- lish if there is a correlation between the amount of the trace ele- ment and the yield. Explain how having the scatterplot referred to above and having the value of r in advance will influence the structure of your statistical test. 5. Carry out and state the conclusion of your test on the correlation. 6. Comment on how well the regression equation will perform based on the results above.
Additive Yield 68.14 93.05 68.38 94.47 68.63 94.1 68.87 93.89 69.12 94.81 69.36 93.32 69.61 94.68 69.83 94.99 71.05 95.99 70.09 97.69 69.92 97.31 67.06 63.64 99.05 99.55 ****** 60.15 100.24
Transcribed Image Text:Additive Yield 68.14 93.05 68.38 94.47 68.63 94.1 68.87 93.89 69.12 94.81 69.36 93.32 69.61 94.68 69.83 94.99 71.05 95.99 70.09 97.69 69.92 97.31 67.06 63.64 99.05 99.55 ****** 60.15 100.24
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