Question

In: Statistics and Probability

year quarter period EMPLOYED INDIVIDUALS (2016-2019) 1 1 1 4169189.0 1 2 2 4262978.0 1 3...

year

quarter

period

EMPLOYED INDIVIDUALS (2016-2019)

1

1

1

4169189.0

1

2

2

4262978.0

1

3

3

4306669.0

1

4

4

4310845.0

2

1

5

4338992.0

2

2

6

4387124.0

2

3

7

4372602.0

2

4

8

4431912.0

3

1

9

4495638.0

3

2

10

4520797.0

3

3

11

4558422.0

3

4

12

4582166.0

4

1

13

4648638.0

4

2

14

4657061.0

4

3

15

4631183.0

4

4

16

4715879.0

        Number of       people

With these time series:

Using time series decomposition, present a seasonally adjusted series for your assigned data (assume the multiplicative model).

Solutions

Expert Solution

Centered
Moving Ratio to Seasonal Data
t Year Quarter Data Average CMA Indexes Deseasonalized
1 1 1 4169189 1.002 41,59,833.1
2 1 2 4262978 1.002 42,56,048.2
3 1 3 4306669 4283646 1.005 0.999 43,11,405.0
4 1 4 4310845 4320389 0.998 0.997 43,22,857.5
5 2 1 4338992 4344149 0.999 1.002 43,29,255.1
6 2 2 4387124 4367524 1.004 1.002 43,79,992.4
7 2 3 4372602 4402238 0.993 0.999 43,77,410.5
8 2 4 4431912 4438528 0.999 0.997 44,44,261.9
9 3 1 4495638 4478465 1.004 1.002 44,85,549.5
10 3 2 4520797 4520474 1.000 1.002 45,13,448.1
11 3 3 4558422 4558381 1.000 0.999 45,63,434.9
12 3 4 4582166 4594539 0.997 0.997 45,94,934.6
13 4 1 4648638 4620667 1.006 1.002 46,38,206.2
14 4 2 4657061 4646476 1.002 1.002 46,49,490.6
15 4 3 4631183 0.999 46,36,275.9
16 4 4 4715879 0.997 47,29,020.2
Calculation of Seasonal Indexes
1 2 3 4
1 1.005 0.998
2 0.999 1.004 0.993 0.999
3 1.004 1.000 1.000 0.997
4 1.006 1.002
mean: 1.003 1.002 1.000 0.998 4.003
adjusted: 1.002 1.002 0.999 0.997 4.000

The graph is:


Related Solutions

year quarter period EMPLOYED INDIVIDUALS (2016-2019) 1 1 1 4169189.0 1 2 2 4262978.0 1 3...
year quarter period EMPLOYED INDIVIDUALS (2016-2019) 1 1 1 4169189.0 1 2 2 4262978.0 1 3 3 4306669.0 1 4 4 4310845.0 2 1 5 4338992.0 2 2 6 4387124.0 2 3 7 4372602.0 2 4 8 4431912.0 3 1 9 4495638.0 3 2 10 4520797.0 3 3 11 4558422.0 3 4 12 4582166.0 4 1 13 4648638.0 4 2 14 4657061.0 4 3 15 4631183.0 4 4 16 4715879.0         Number of       people With these time series: Use regression...
year quarter period EMPLOYED INDIVIDUALS (2016-2019) 1 1 1 4169189.0 1 2 2 4262978.0 1 3...
year quarter period EMPLOYED INDIVIDUALS (2016-2019) 1 1 1 4169189.0 1 2 2 4262978.0 1 3 3 4306669.0 1 4 4 4310845.0 2 1 5 4338992.0 2 2 6 4387124.0 2 3 7 4372602.0 2 4 8 4431912.0 3 1 9 4495638.0 3 2 10 4520797.0 3 3 11 4558422.0 3 4 12 4582166.0 4 1 13 4648638.0 4 2 14 4657061.0 4 3 15 4631183.0 4 4 16 4715879.0         Number of       people With these time series: Present a...
The following production budget for the four quarters of 2019: Quarter 1 Quarter 2 Quarter 3...
The following production budget for the four quarters of 2019: Quarter 1 Quarter 2 Quarter 3 Quarter 4 Units 3,000 4,000 5,000 8,000 Each units requires 4 kg of raw materials costing $6 per kilogram. On December 31, 2018, the ending inventory of raw materials was 3,000 kg. Management wants to have a raw materials inventory at the beginning of each quarter equal to 25% of the current quarter's production requirements in units. The production budget for the first quarter...
  Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1 2   Budgeted unit sales...
  Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1 2   Budgeted unit sales 50,000 65,000 115,000 70,000 80,000 90,000   Selling price per unit $7 per unit             1 Chapter 7: Applying Excel 2 3 Data Year 2 Quarter Year 3 Quarter 4 1 2 3 4 1 2 5 Budgeted unit sales 50,000 65,000 115,000 70,000 80,000 90,000 6 7 � Selling price per unit $8 per unit 8 � Accounts receivable, beginning balance...
Chapter 9: Applying Excel Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1...
Chapter 9: Applying Excel Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1 2 Budgeted unit sales 40,000 60,000 100,000 50,000 70,000 80,000 • Selling price per unit $8 per unit • Accounts receivable, beginning balance $65,000 • Sales collected in the quarter sales are made 75% • Sales collected in the quarter after sales are made 25% • Desired ending finished goods inventory is 30% of the budgeted unit sales of the next quarter • Finished...
Chapter 8: Applying Excel Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1...
Chapter 8: Applying Excel Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1 2 Budgeted unit sales        40,000         60,000      100,000      50,000         70,000         80,000 • Selling price per unit $8 per unit • Accounts receivable, beginning balance $65,000 • Sales collected in the quarter sales are made 75% • Sales collected in the quarter after sales are made 25% • Desired ending finished goods inventory is 30% of the budgeted unit sales...
Quarter Year 1 Year 2 Year 3 1 5 8 10 2 1 3 7 3...
Quarter Year 1 Year 2 Year 3 1 5 8 10 2 1 3 7 3 3 6 8 4 7 10 12 (A) What type of pattern exists in the data? a. Positive trend, no seasonality b. Horizontal trend, no seasonality c. Vertical trend, no seasonality d. Positive tend, with seasonality e. Horizontal trend, with seasonality f. Vertical trend, with seasonality (B) Use a multiple regression model with dummy variables as follows to develop an equation to account for...
Research the U.S. economic growth AND unemployment rates for the same 3-year period (2016-2019) and explain...
Research the U.S. economic growth AND unemployment rates for the same 3-year period (2016-2019) and explain why the Fed has raised the interest rate as shown in the picture. Also, predict what might happen to the Fed interest rate for the rest of 2019, and explain why.
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 3 6...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 3 6 7 2 4 1 8 3 1 7 5 4 5 7 8 a. Which of the following is a time series plot? - Select your answer -time series plot #1time series plot #2time series plot #3Item 1 What type of pattern exists in the data? - Select your answer -upward linear trendnonlinear trend and a seasonal patternlinear trend and a seasonal patternslight curvaturedownward...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 3 6...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 3 6 8 2 2 4 8 3 4 7 9 4 6 9 11 . (a)  Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1 if Quarter 2, 0 otherwise; Qtr3 = 1 if Quarter 3, 0 otherwise. If required, round your...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT