Barbara Lynch is the product manager for a line of skiwear produced byHeathCoIndustries and privately branded for sale under several different names, including Northern Slopes and JacqueMonri. A new part of Ms. Lynchs job is to provide a quarterly forecast of sales for the northern United States: a10-year sales history is shownbelow:(c4p11)

Sales ($000)

Year

1st Quarter

2nd Quarter

3rd Quarter

4th Quarter

2007

$ 72,962

$ 81,921

$ 97,729

$ 142,161

2008

145,592

117,129

114,159

151,402

2009

153,907

100,144

123,242

128,497

2010

176,076

180,440

162,665

220,818

2011

202,415

211,780

163,710

200,135

2012

174,200

182,556

198,990

243,700

2013

253,142

218,755

225,422

253,653

2014

257,156

202,568

224,482

229,879

2015

289,321

266,095

262,938

322,052

2016

313,769

315,011

264,939

301,479

a)Ms. Lynch has hired you to help with the forecasting effort. First, she would like you to prepare a time-series plot of the data and to write her a memo indicating what the plot appears to show and whether it seems likely that a simple linear trend would be useful in preparing forecasts.

The plot of the sales datashowan upward trend and some seasonality. A linear trend model should capture the overall movement in sales but will not capture what appears to be seasonal fluctuations.

b)Do your regression results indicate to you that there is a significant trend to the data? Explain why or why not.

The results show a significant positive trend as demonstrated by the Excel regression results below. Since the graph indicates upward movement in the sales data a positive trend is expected and thus a one tailed t-test is appropriate. We see the t-Stat is VERY large and P/2 = 0.000.

Coefficients

Std Error

t Stat

P-value

P/2

Intercept

88,741.012

8,043.906

11.032

0.000

0.000

Time

5,362.623

341.907

15.684

0.000

0.000

To see more about developing a linear regression model, please watch thisYouTube video.

In this assignment you are to act as the manager of theMid-Valley Travel Agency (MVTA), which hasoffices in 12 cities. The company believes that its monthly airline bookings are related to the mean income in those cities and has collected the following data:(c4p10)

Location

Bookings

Income

Location

Bookings

Income

1

1,098

43,299

7

855

27,482

2

1,131

45,021

8

1,054

33,025

3

1,120

40,290

9

1,081

34,687

4

1,142

41,893

10

982

28,725

5

971

30,620

11

1,098

37,892

6

1,403

48,105

12

1,387

46,198

1.Develop a linear regression model of monthly airline bookings as a function of income.

2.Develop a scatter plot of the data and trend line.

3.Use the process describedabove toevaluate your results.

4.How would you state your findings to upper management?