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Lexon Inc. is a large manufacturer of affordable DVD players. Management recently became aware of rising expenses resulting from returns of malfunctioning products. As a starting point for further analysis, Paige Jennings, the controller, wants to test different forecasting methods and then use the best one to forecast quarterly expenses for 2019. The relevant quarterly data for the previous three years follow:

2016 Quarter	Return Expenses			2017 Quarter	Return Expenses			2018 Quarter	Return Expenses
1	$	13,400		1	$	13,700		1	$	14,300
2		12,100		2		12,900		2		13,200
3		12,400		3		12,500		3		13,000
4		14,600		4		15,000		4		15,700

The result of a simple regression analysis using all 12 data points yielded an intercept of $12,634.85 and a coefficient for the independent variable of $143.36. (R-squared = 0.46, SE = $1,042.49.)

Required:

1. Plot the data in the order of the dates. (To earn full credit for this graph you must plot all required points for each curve. While plotting the points a tool icon will pop up. You can use this to enter exact co-ordinates for your points as needed.)

2. Looking at the graph you prepared for requirement 1, select two representative data points and calculate the quarterly forecast for 2019 using the high-low method.

3. Calculate the quarterly forecasts for 2019 using the results of a regression analysis. Evaluate the results of the regression analysis and make appropriate changes to improve the model.