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##### PART I: Calculate the mean yearly value using t...

**Description**

Solution

**Question**

PART I: Calculate the mean yearly value using the average gas prices by month found in the ?Final Project Data Set.? Using the years as your x-axis and the annual mean as your y-axis, create a scatterplot and a linear regression line. Answer the following questions using your scatterplot and linear regression line: What is the slope of the linear regression line? What is the Y-intercept of the linear regression line? What is the equation of the linear regression line in slope-intercept form? Based on the linear regression line, what would be an estimated cost of gas in the year 2020? What are the residuals of each year? Select a current price that you have seen or paid recently for gas. Is that price within the range of the linear regression line or is it an outlier? Is it within the confidence interval of 5% or either end? Part I must be provided as an Excel spreadsheet. It must be complete and show all work, not just a final amount or answer The following attachment is needed to answer the questions.,Hi Natalia, You said you need a recent price of gas that I have paid recently to complete the last question of the assignment. I recently paid $3.87 per gallon for regular gasoline.,Hi Natalia, I am willing to pay an additional $50 for you to complete part II based off the work you did for part one. PART II: Imagine that you are a manager at a delivery service and you are creating a report to project the effects on your company of rising gas prices in the next ten years. Using the preceding statistical analysis as your basis to support your claims. Include the following considerations: Introduce the project and its significance to the company. Explain the statistical analysis that you completed in Part I. Be sure to explain where the data came from, what analysis was done, and what the results were. Give conclusions that you have drawn from the data. Consider the effects of your gas price predictions on the delivery business. Also consider whether or not you believe your predicted gas prices are accurate. What could occur in the future that would change your linear regression line and therefore your prediction?,Hi Natalia, I just posted the second part of the question in a new thread. Did you get the information I sent you about what I recently paid for a gallon of gas? You needed that in order to complete the 1st part of the assignment

Paper#13423 | Written in 18-Jul-2015

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