he fish in my pond have mean length 14 inches with a standard deviation of 2 inches and mean weight 4 pounds with a standard deviation of .8 pounds.  The correlation coefficient of length and weight is .7.  If the length of a particular randomly selected fish is reported to be 17 inches, and if we use simple linear regression to predict the weight of a fish whose length is reported to be 15.8 inches long, then what is the expected squared error?

The fish in my pond have mean length 10 inches and mean weight 4 pounds. The correlation coefficient of length and weight is .9. If the length of a particular randomly selected fish is reported to be 10 inches, then what should we predict for the weight of that fish using simple linear regression? 4 10 2.5 NOT ENOUGH INFORMATION GIVEN NONE OF THE OTHERS

A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data and summary statistics (including the averages, standard deviations and the correlation coefficient) are shown in the table. If the "price per kilogram" is the predictor variable and "kilograms sold" is the response variable, then use a regression line to predict the the amount of kilograms sold for a "price per kilogram" equal to $15.   Round your numbers to 3 decimal places.

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There is a dataset of size n = 51 and is for the 50 states and the District of Columbia in the United States. The dependent variable is year 2002 birth rate per 1000 females 18 to 19 years old and independent variable is the violent crime rate (per 1000 population). A simple linear regression model is run with the results given below. What is the Pearson correlation coefficient between x and y variables? The R squared of the model? What kind of relationship there is?

A researcher is interested in examining the relationship between spousal abuse and child abuse.  Specifically, they are interested in determining whether there is a predictive relationship between spousal abuse and child abuse in 5 county social services offices.  Calculate the linear regression line for the following data.  Note you have already calculated the first step to this analysis (Pearson's Correlation)

Let's study the relationship between brand, camera resolution, and internal storage capacity on the price of smartphones. Use α = .05 to perform a regression analysis of the Smartphones01CS dataset, and then answer the following questions. When you copy and paste output from MegaStat to answer a question, remember to choose to "Keep Formatting" to paste the text. a. Did you find any evidence of multicollinearity and variance inflation among the predictors. Explain your answer using a VIF analysis. b. Copy and paste the normal probability plot for your analysis. Is there any evidence that the errors are not normally distributed? Explain. c. Copy and paste the Residuals vs. Predicted Y-values. Does the pattern support the null hypothesis of constant variance for the errors? Explain. d. Study the residuals analysis. Which observations, if any, have unusual residuals? e. Study the residuals analysis. Calculate the leverage statistic. Which observations, if any, are high leverage…

Consider a certain data set on shoulder girth and height of a group of individuals. The mean shoulder girth is 107.20 cm with a standard deviation of 10.37 cm. The mean height is 171.14 cm with a standard deviation of 9.41 cm. The correlation between height and shoulder girth is 0.67. Calculate R2 of the regression line for predicting height from shoulder girth, and interpret it in the context of the application.