This data can be modeled by the equation y = 0.84r + 4.11. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. A) How many murders per 100,000 residents can be expected in a state with 6.6 thousand automatic weapons? Answer - Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 10.2 thousand automatic weapons?

A biology student is investigating the claim that the temperature can be predicted by counting cricket chirps. She has found a linear regression equation T=42.2+0.21r, where T is the temperature in degrees Fahrenheit and r is the number of chirps per minute. What is the predicted temperature for 90 chirps per minute?   18.9 degrees 227.6 degrees 23.3 degrees 61.1 degrees

Provide an example of a research project in your hometown where you would choose to use linear regression. What variable would be your Y-score, and what variable would be your X-score? What does a regression line represent? What is the standard error of estimate?

A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures. ŷ = 21 + 10x, + 8x2 where x, = inventory investment ($1,000s) X2 = advertising expenditures ($1,000s) y = sales ($1,000s). (a) Predict the sales (in dollars) resulting from a $15,000 investment in inventory and an advertising budget of $11,000. %24 (b) Interpret b, and b, in this estimated regression equation. Sales can be expected to increase by $ for every dollar increase in inventory investment when advertising expenditure is held constant. Sales can be expected to increase by $ for every dollar increase in advertising expenditure when inventory investment is held constant.

A marketing consultant created a linear regression model to predict the number of units sold by a client based on the amount of money spent on marketing by the client. Which of the following is the best graphic to use to evaluate the appropriateness of the model?

Use Excel to Run the Regressions:1. Wage and Age: Do you think a worker’s wage is related to his/her age? It is expected that wagesincrease with age up to certain age, after that wages go down. The “Wage Quadratic Data” fileposted contains data on the hourly wage (in $) for construction workers, workers’ ageand whether the worker has a bachelor’s degree or not (Graduate equals 1 if the worker has abachelor’s degree and 0 otherwise). Use the data file to answer the following questions:A) Build a model to predict the hourly wage of construction workers based on their education andage.B) Use the model to predict the hourly wage for a college graduate construction worker if his/herage is 30, 50, and 70c) Based on your model, calculate the age at which the hourly wage for construction workers ismaximized.

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