The production of wine is a multibillion-dollar worldwide industry. In an attempt to develop a model of wine quality as judged by wine experts, data was collected from red wine variants. A sample of 20 wines is provided in the accompanying table. Develop a multiple linear regression model to predict wine quality, measured on a scale from 0 (very bad) to 10(excellent) based on alcohol content (%) and the amount of chlorides.
Alcohol | Chlorides |
10.1 | 0.067 |
11.8 | 0.064 |
9 | 0.076 |
9.6 | 0.097 |
12.8 | 0.078 |
9.7 | 0.077 |
9.6 | 0.091 |
9.5 | 0.073 |
10.6 | 0.071 |
9.4 | 0.077 |
10.6 | 0.105 |
10.5 | 0.074 |
10.8 | 0.07 |
10.5 | 0.084 |
11.3 | 0.174 |
10.7 | 0.076 |
10.5 | 0.065 |
9.5 | 0.069 |
10.8 | 0.055 |
10.6 | 0.077 |
11.2 | 0.055 |
9.5 | 0.089 |
11 | 0.067 |
9.9 | 0.11 |
13.1 | 0.076 |
12.5 | 0.072 |
9.6 | 0.091 |
9.7 | 0.082 |
11.5 | 0.091 |
9.2 | 0.085 |
14 | 0.065 |
11.1 | 0.058 |
10 | 0.053 |
10.8 | 0.081 |
11.6 | 0.077 |
9.6 | 0.073 |
9.7 | 0.078 |
9.9 | 0.073 |
11.3 | 0.053 |
9.8 | 0.094 |
11.6 | 0.086 |
9.9 | 0.145 |
9.9 | 0.147 |
9.5 | 0.089 |
11.6 | 0.077 |
11 | 0.067 |
10 | 0.061 |
9.8 | 0.267 |
14 | 0.044 |
9 | 0.086 |
Quality |
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6 |
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8 |
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4 |
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The production of wine is a multibillion-dollar worldwide industry. In an attempt to develop a model...
The production of wine is a multibillion-dollar worldwide industry. In an attempt to develop a model of wine quality as judged by wine experts, data was collected from red wine variants. A sample of 20 wines is provided in the accompanying table. Develop a multiple linear regression model to predict wine quality, measured on a scale from 0 (very bad) to 10 (excellent) based on alcohol content (%) and the amount of chlorides. Complete parts a through g below. Quality Alcohol_Content(%) Chlorides0 7.1 0.0610 7.6 0.0632...
URGENT PLEASE HELP The production of wine is a multibillion-dollar worldwide industry. In an attempt to develop a model of wine quality as judged by wine experts, data was collected from red wine variants. A sample of 20 wines is provided in the accompanying table. Develop a multiple linear regression model to predict wine quality, measured on a scale from 0 (very bad) to 10 (excellent) based on alcohol content (%) and the amount of chlorides. Complete parts a through...
The production of wine is a multibillion dollar worldwide industry. In an attempt to develop a model of wine quality as judged by wine experts, data was collected from red wine variants. A sample of 20 wines is provided in the accompanying table. Develop a multiple linear regression model to predict w ne quality, measured on a scale from 0 very bad to 10 excellent based on a cohol content(%) and the amount of chlo dos. Complete parts a through...
The production of wine is a multi-billion-dollar worldwide industry. In an attempt to develop a model of wine quality as judged by wine experts, data was collected from red wine variants from a particular type of foreign wine. A multiple linear regression model was developed from a sample of 45 wines. The model was used to predict wine quality, measured on a scale from 0 (very bad) to 10 (excellent) based on the alcohol content (%) and the amount of...
The production of wine is a multi-billion-dollar worldwide industry. In an attempt to develop a model of wine quality as judged by wine experts, data was collected from red wine variants from a particular type of foreign wine. A multiple linear regression model was developed from a sample of 45 wines. The model was used to predict wine quality, measured on a scale from 0 (very bad) to 10 (excellent) based on the alcohol content (%) and the amount of...
use the attached data set to plot graph using regression in python 4 1 fixed acid volatile ac citric acid residual sichlorides free sulfu total sulfu density pHsulphates alcoholquality type 34 0.9978 3.51 0.56 1.9 0.076 0 2.6 0.098 25 5 red 3.2 0.68 7.8 0.88 67 0.9968 54 0.997 3.26 0.65 17 60 0.998 3.16 0.58 9.8 7.8 0.760.04 2.3 0.092 11.20.28 1.9 0.075 0 1.9 0.076 11 34 0.9978 3.51 0.569.4 5 red 7.4 0.66 0 1.8 0.05...
Compute the correlation coefficient, r, for all five variables (columns). Interpret your findings whether you have determined any relationship between variables. X1 X2 X3 X4 X5 The data (X1, X2, X3, X4, X5) are by city. 8 78 284 9.1 109 X1 = death rate per 1000 residents 9.3 68 433 8.7 144 X2 = doctor availability per 100,000 residents 7.5 70 739 7.2 113 X3 = hospital availability per 100,000 residents 8.9 96 1792 8.9 97 X4 = annual...
Compute Regression Analysis for following relationship: The relationship between death rate X1 (USD) vs. population density X5. Population as a Predictor, X, then death rate as a Response variable, Y. Get Regression Output, and Scatter plot between these variables and compute Coefficient of Determination, R2, and Interpret your findings. X1 X2 X3 X4 X5 The data (X1, X2, X3, X4, X5) are by city. 8 78 284 9.1 109 X1 = death rate per 1000 residents 9.3 68 433 8.7 144...
Determine the Capacitance in uF (micro-Farads) of the system below using the data, graph and tolerance graph below. R -ww G(s) 1/(RCs+1) ei R =1000 ohms 1 Slope T c(t) c() = 1 - e-(1/T B 0.632 Tolerance graph (Ts(2%) = 4*T): A A 4T 2T 3T 5T 63.2% 86.5% 95% 98.2% Of output 99.3% 0.75 0.5 Output curve: 0.25 0 0 0.025 0.05 0.075 0.1 0.125 Data: x(time) y(amplitude) 0.001 0.09516258196 0.002 0.1812692469 0.2591817793 0.003 0.329679954 0.004 0.3934693403 0.005...
information is in order last two screen shots are appendix. Hercules Exercise Equipment Co. purchased a computerized measuring device two years ago for $96,000. The equipment falls into the five- year category for MACRS depreciation and can currently be sold for $43,800. A new piece of equipment will cost $320,000. It also falls into the five-year category for MACRS depreciation. Assume the new equipment would provide the following stream of added cost savings for the next six years. Use Table...