Prepare a time-series plot of data

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1. CoastCo Insurance, Inc., is interested in forecasting annual larceny thefts in the United States using the following data:

Year

Larceny
Thefts*

Year

Laetetty

Thefts*

6,592

6,926

t972
1973

 

1984
P965

1974

5,263

1986

7,257

1975

5.9713

1987

7,SM

1976

6.271

1988

7,706

1977

5,906

1989

7,1372

1978

5,083

1998

7,946

1979

6,578

1991

8,142

1980

7,137

1992

7,915

1981

7,194

1993

7,021

1982

7.143

1994

7,876

1983

6,713

 

 


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 structure of larceny thefts for lags of 1, 2, 3, 4, and 5. Do the autocorrelation coef?cients fall quickly toward zero? Demonstrate that the critical value for rk is 0.417. Explain what these results tell you about a trend in the data.

c. On the basis of what is found in parts a and b, suggest a forecasting method from Table 2.1 that you think might be appropriate for this series.

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

 

Quarter

 

Q1

Q2

Q3

Q4

1981

'54.9

70.1

65 8

50 2

1982

53.3

67 9

63 1

55 3

1983

613

811

817

691

1984

67.8

82.7

79 0

661

1985

62 3

79.3

76 5

65 S

 

1986

58.1

66 8

63 4

56 I

1987

51.9

628

647

53S

1988

187.0

605

99 2

51 6

1989

48.1

5S 1

59 3

44 5

1990

43 3

51 7

50 5

42 6

1991

354

474

472

 

409

1992

430

52.8

570

576

1993

56 4

64 3

62 1

66 4

1994

691

78.7

78.7

775

1995

79 2

86 8

87.6

664

On the basis of your analysis, do you think there is a signi?cant trend in MHS? Is there seasonality? What forecasting methods might be appropriate for MHS according to the guidelines in Table 2.1?

3. Home sales are often considered an important determinant of the future health of the economy. Thus, there is widespread interest in being able to forecast total houses sold (THS). Quarterly data for THS are shown in the following table in thousands of units:

1233_data.png

a. Prepare a time-series plot of THS. Describe what you see in this plot in terms of trend and seasonality.

b. Calculate and plot the ?rst twelve autocorrelation coef?cients for PHS. What does this autocorrelation structure suggest about the trend?

c. De-trend the data by calculating ?rst differences: DTHSt THSt THSt1. Calculate and plot the ?rst eight autocorrelation coef?cients for DTHS. Is there a trend in DTHS?

4. Question 1 includes data on the Japanese exchange rate (EXRJ) by month. On the basis of a time-series plot of these data and the autocorrelation structure of EXRJ, would you say the data are stationary? Explain your answer.

Reference no: EM13740739

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