SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Statistics Regression Residual Total Intercept Crime Rate (per 100,000) Violent crimes (per 100,000) Property Crimes (per 100,000) 0.44834 0.201008 0.145732 5.163609 50 df 3 47 50 SS MS F Significance F 315.2655861 105.0885 5.912074 0.00168624 1253.154414 26.66286 1568.42 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 92.75449 3.353599979 27.65819 9.91E-31 86.0079172 99.50106 86.0079172 99.5010631 -0.011007 0.006981811 -1.57647 0.121626 -0.02505218 0.003039 -0.02505218 0.00303901 0 65535 #NUM! 0.0085 0.007979244 1.065228 #NUM! -0.00755246 0.024552 -0.00755246 0.02455188 0 0 0 0 0

Refer to the data set:Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 5.

Define the different ways to use linear regression?

Can you please tell also the test statistics and if the weight is close to 518 pounds?

The number of megapixels in a digital camera is one of the most important factors in determining picture quality. But, do digital cameras with more megapixels cost more? The following data show the number of megapixels and the price ($) for 10 digital cameras(Consumer Reports, March 2009). Use these data to develop an estimated regression equation that can be used to predict the price of a digital camera given the number of megapixels. Brand and Model Megapixels Price (S) Canon PowerShot SD1100 IS Casio Exilim Card EX-510 8 180 200 230 10 Sony Cyber-shot DSC-T70 Pentax Optio M50 Canon PowerShot G10 120 470 15 8 Canon PowerShot A590 IS Canon PowerShot El 140 180 10 12 Fujifilm FinePix FOOFD Sony Cyber-shot DSC-W170 Canon PowerShot A470 310 10 250 110

A linear regression equation has a slope of 4 and an intercept of 2. What is the predicted value of Y for an X of 8? Edit View Insert Format Tools Table

Corvette, Ferrari, and Jaguar produced a variety of classic cars that continue to increase in value. The data showing the rarity rating (1–20) and the high price (1000ドルs) for 15 classic cars is contained in the Excel Online file below. Construct a spreadsheet to answer the following questions. Open spreadsheet Develop a scatter diagram of the data using the rarity rating as the independent variable and price as the dependent variable. Does a simple linear regression model appear to be appropriate? A simple linear regression model _________appearsdoes not appear to be appropriate. Develop an estimated multiple regression equation with rarity rating and as the two independent variables. (to whole numbers) What is the value of the coefficient of determination? Note: report between 0 and 1. (to 3 decimals) What is the value of the test statistic? (to 2 decimals) What is the -value? (to 4 decimals) Consider the nonlinear relationship shown by equation ....

Write a short note on regression analysis

Please answer parts d, e and f.

help asap please. I will upvote.

The applet displays a scatterplot with the following points: (7,10),(27,35),(24,25),(8,12),(10,19),(15,22). Identify the slope of the regression line, intercept of the regression line, and correlation coefficient. Report your answers accurate to within two decimal places.

Refer to the data set:(-1, 2), (1, 3), (1, 5), (2, 7), (3, 8), (4, 11)Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 10

The file Galton on D2L contains the 928 observations Francis Galton used in 1885 to estimate the relationship between the heights of parents and the heights of their children. The column Children refers to the height (in inches) of a child, and the column Mid-Parents refers to the average height (in inches) of the mother and father of that child. You can download this file into Excel and Minitab. a. Calculate the regression Height of Children = a +b (Height of Mid-Parents). b. Calculate the average for Height of Children, and calculate the average Height of Mid-Parents. c. Create a new variable in Minitab which is the Height of Children measured in terms of deviations from its mean. Call this new variable y. Also, create a new variable in Minitab with is the Height of Mid-Parents measured in terms of deviations from its mean. Call this new variable x. Calculate the regression y = a + bx. You can create the new y and x variables in Excel of Minitab, whichever you find more convenient....