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The income of farmers depends on various factors. To predict the income of the next year, a study was undertaken and data was gathered considering as many as possible factors that might influence the yearly income. Regression methods are used to create such a prediction function, that is, we want to predict the profit for the next year. The following were determined. X₁ = SIZE - farm size recorded x 1000 hectares X₂ AGE - how long the farm has been in operation in years = X3 = RATIO - the ratio of land size to field size recorded as 0.5, 0.75, 0.8 and 0.9 X4 = METHOD - rotational and non rotational method of planting Ý INCOME the income per year recorded in x R 1 000 000.00 The partial dataset is as follows INCOME Y 1.3 2.4 3.2 1.5 2.1 a. C. Standardized Residual Sample Quantiles 15 1.0- 0.8- 0.6- 0.4- 02- 0.0- 20 SIZE X₁ 25 5 8 2 1.2 1.5 Predicted 45 ܝܕܕܢ ܥܗ Theoretical Quantiles 1.1. The analyst did some exploratory analysis and below are some of the residual plots he constructed. Study the plots and answer the questions that follows. AGE X₂ 2 20 100 80 50 11 b. 3 Standardized Residual RATIO X3 41 0.5 0.75 0.8 0.8 0.75 100 120 140 160 180 METHOD X4 Rotational Predicted Rotational Non-rotational Rotational Non-rotational Diagnose each of the possible problems that are displayed in the plots. If applicable also mention a formal way to test that it is indeed a problem. Also, when a problem is diagnosed, provide a possible remedial measure to remedy the problem.

The income of farmers depends on various factors. To predict the income of the next year, a study was undertaken and data was gathered considering as many as possible factors that might influence the yearly income. Regression methods are used to create such a prediction function, that is, we want to predict the profit for the next year. The following were determined. X₁ = SIZE - farm size recorded x 1000 hectares X₂ AGE - how long the farm has been in operation in years = X3 = RATIO - the ratio of land size to field size recorded as 0.5, 0.75, 0.8 and 0.9 X4 = METHOD - rotational and non rotational method of planting Ý INCOME the income per year recorded in x R 1 000 000.00 The partial dataset is as follows INCOME Y 1.3 2.4 3.2 1.5 2.1 a. C. Standardized Residual Sample Quantiles 15 1.0- 0.8- 0.6- 0.4- 02- 0.0- 20 SIZE X₁ 25 5 8 2 1.2 1.5 Predicted 45 ܝܕܕܢ ܥܗ Theoretical Quantiles 1.1. The analyst did some exploratory analysis and below are some of the residual plots he constructed. Study the plots and answer the questions that follows. AGE X₂ 2 20 100 80 50 11 b. 3 Standardized Residual RATIO X3 41 0.5 0.75 0.8 0.8 0.75 100 120 140 160 180 METHOD X4 Rotational Predicted Rotational Non-rotational Rotational Non-rotational Diagnose each of the possible problems that are displayed in the plots. If applicable also mention a formal way to test that it is indeed a problem. Also, when a problem is diagnosed, provide a possible remedial measure to remedy the problem.

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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The income of farmers depends on various factors. To predict the income of the next year, a study was undertaken and data was gathered considering as many as possible factors that might influence the yearly income. Regression methods are used to create such a prediction function, that is, we want to predict the profit for the next year. The following were determined. X₁ = SIZE - farm size recorded × 1000 hectares X₂ AGE - how long the farm has been in operation in years X3 = RATIO - the ratio of land size to field size recorded as 0.5, 0.75, 0.8 and 0.9 X4 = METHOD - rotational and non rotational method of planting Ŷ INCOME the income per year recorded in × R 1 000 000.00 The partial dataset is as follows INCOME Y 1.3 2.4 3.2 1.5 2.1 a. C. Standardized Residual Sample Quantiles 15 1.0- 0.8- 0.6- 0.4- 0.2- 0.0- 20 SIZE X₁ 25 5 8 2 1.2 1.5 Predicted Theoretical Quantiles. 45 AGE X₂ 1.1. The analyst did some exploratory analysis and below are some of the residual plots he constructed. Study the plots and answer the questions that follows. 2 20 100 80 50 11 b. 3 RATIO X3 Standardized Residual 0.5 0.75 0.8 0.8 0.75 80 100 120 140 160 180 METHOD X4 Rotational Predicted Rotational Non-rotational Rotational Non-rotational Diagnose each of the possible problems that are displayed in the plots. If applicable also mention a formal way to test that it is indeed a problem. Also, when a problem is diagnosed, provide a possible remedial measure to remedy the problem.
Transcribed Image Text:The income of farmers depends on various factors. To predict the income of the next year, a study was undertaken and data was gathered considering as many as possible factors that might influence the yearly income. Regression methods are used to create such a prediction function, that is, we want to predict the profit for the next year. The following were determined. X₁ = SIZE - farm size recorded × 1000 hectares X₂ AGE - how long the farm has been in operation in years X3 = RATIO - the ratio of land size to field size recorded as 0.5, 0.75, 0.8 and 0.9 X4 = METHOD - rotational and non rotational method of planting Ŷ INCOME the income per year recorded in × R 1 000 000.00 The partial dataset is as follows INCOME Y 1.3 2.4 3.2 1.5 2.1 a. C. Standardized Residual Sample Quantiles 15 1.0- 0.8- 0.6- 0.4- 0.2- 0.0- 20 SIZE X₁ 25 5 8 2 1.2 1.5 Predicted Theoretical Quantiles. 45 AGE X₂ 1.1. The analyst did some exploratory analysis and below are some of the residual plots he constructed. Study the plots and answer the questions that follows. 2 20 100 80 50 11 b. 3 RATIO X3 Standardized Residual 0.5 0.75 0.8 0.8 0.75 80 100 120 140 160 180 METHOD X4 Rotational Predicted Rotational Non-rotational Rotational Non-rotational Diagnose each of the possible problems that are displayed in the plots. If applicable also mention a formal way to test that it is indeed a problem. Also, when a problem is diagnosed, provide a possible remedial measure to remedy the problem.
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