Linear Regression Use linear regression to find the equation for the linear function that best fits this data. Round both numbers to two decimal places. Write your final answer in a form of an equation y = mx + b y 1 68 2 3 4 5 6 92 109 136 150 170

A regression was run to determine whether there is arelationship between the diameter of a tree (x, in inches) and the tree’s age (y, in years). Theresults of the regression are given below. Use this topredict the age of a tree with diameter 10 inches. y=ax+ba=6.301b=1.044r=0.970

Depreciation A sandwich shop purchases a used pizza oven for $875. After 5 years, the oven will have to be discarded and replaced. Write a linear equation giving the value V of the equipment during the 5 years it will be in use.

Linear Regression - Christmas Trees The following table gives the total number of live Christmas trees sold, in millions, in the United States from 2004 to 2011. (Source: Statista.com). t = number of years since 2004 C = total number of Christmas trees sold in the U.S. (in millions) 1. Use the TABLE to determine the number of live Christmas trees sold in the year 2008. In 2008, there were approximately с 0 = 27.1 2 28.6 4 28.2 6 27 7 30.8 2. Determine the linear regression equation that models the set of data above. Use the indicated variables and proper function notation. Round to the nearest hundredth as needed. million live Christmas trees sold in the U.S. 3. Interpret the meaning of the slope of your (rounded) regression model. From 2004 to 2011, the number of Christmas trees sold in the U.S. increased by approximately million trees each year. 4. Use the REGRESSION EQUATION to determine the number of live Christmas trees sold in the year 2008. In 2008, there were approximately 5.…

Linear RegressionUse linear regression to find the equation for the linear function that best fits this data. Round both numbers to two decimal places. Write your final answer in a form of an equation ˆy=mx+b x 1 2 3 4 5 6 y 89 112 133 151 158 188 ˆy=

Linear Regression Use linear regression to find the equation for the linear function that best fits this data. Round both numbers to two decimal places. Write your final answer in a form of an equation y = mx + 6 2 3 4 y 80 93 111 128 141 167

Perform Linear Regression Analysis by Octave (or MatLab) software using formulas for calculation of required parameters. Make the graph y versus x values and ytted VS. X on the same plot. x Answers: 0.05 0.04 35.7210 23.3960 7 0.03 13.3970 X S 0.02 6.0310 0.01 1.5190 0 0.0000

Linear Regression Use linear regression to find the equation for the linear function that best fits this data. Round both numbers to two decimal places. Write your final answer in a form of an equation y = mx + b 5 6 1 2 3 4 У 95 111 133 155 170 186

persor Develop an estimated multiple regression equation that relates risk of a stroke to the person's age, systolic blood pressure, and whethet Let xi represent the person's age. Let x2 represent the person's systolic blood pressure. Let represent whether the person is a smoker. If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sgn even d there is a sign before the blank. (Example -300)

The data provided give the number of standby hours based on total staff present, X₁, and remote hours, X₂. Perform a multiple regression analysis using the data provided and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity? Click the icon to view the data. Determine the VIF for each independent variable in the model. | VIF ₂2 = VIF₁ = (Round to three decimal places as needed.) Is there reason to suspect the existence of collinearity? OA. No. The VIF for each independent variable is less than 5. B. Yes. The VIF for each independent variable is greater than 5. OC. No. The VIF for each independent variable is greater than 5. OD. Yes. The VIF for each independent variable is less than 5. wwwwwww Table of Data Standby Total Staff Hours Present 245 330 274 358 195 197 117 153 115 275 200 236 336 339 321 303 286 329 352 323 Remote Hours 417 655 524 385 349 350 388 153 278 479 Print Done