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Problem 1: Coast Insurance, Inc. is interested in forecasting annual larceny theft in the United States using the following data

 Year

Larceny Theft*

Year

Larceny Theft*

1972

4,151

1984

6,592

1973

4,348

1985

6,926

1974

5,263

1986

7,257

1975

5,978

1987

7,500

1976

6,271

1988

7,706

1977

5,906

1989

7,872

1978

5,983

1990

7,946

1979

6,578

1991

8,142

1980

7,137

1992

7,915

1981

7,194

1993

7,821

1982

7,143

1994

7,876

1983

6,713

 

 

* Data are in thousands

Source: U.S Bureau of the Census

a. Prepare a time-series plot of these data. On the basis of this graph, do you think there is a trend in the data? Explain.

b. Look at the autocorrelation structures of larceny theft for lags of 1, 2, 3, 4, and 5. Do the autocorrelation coefficients fall quickly toward zero? Demonstrate that the critical value for rk is 0.417. Explain what these result tell you about a trend in the data.

c. On the basis of what is found in parts a and b, suggest a forecasting methods from Table that you think might be appropriate for this series.

Problem 2: Use exploratory data analysis to determine whether there is a trend and/or seasonality in mobile home shipments (MHS). The data by quarter are shown in the following table:

Year

Q1

Q2

Q3

Q4

1981

54.9

70.1

65.8

50.2

1982

53.3

67.9

63.1

55.3

1983

63.3

81.5

81.7

69.2

1984

67.8

82.7

79.0

66.2

1985

62.3

79.3

76.5

65.5

1986

58.1

66.8

63.4

56.1

1987

51.9

62.8

64.7

53.5

1988

47.0

60.5

59.2

51.6

1989

48.1

55.1

50.3

44.5

1990

43.3

51.7

50.5

42.6

1991

35.4

4.4

47.2

40.9

1992

43.0

52.8

57.0

57.6

1993

56.4

64.3

67.1

66.4

1994

69.1

78.7

78.7

77.5

1995

79.2

86.8

87.6

86.4

On the basis of your analysis, do you think is a significant trend in MHS? There seasonality? What forecasting methods might be appropriate for MHS according to the guideline in Table?

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