Question

Use the data below to answer this questions.

a.) Generate a scatter of the data

b. ) Report the monthly averages (January for all years, February for all years etc.)

c.) Is there seasonality? Is there a trend?

d.) How can you forecast the value for March 2020? Generate that forecast.

e.) (Not technical) This forecast will for sure be wrong. Why?

Reference period	Employment 3
	Persons
Jan-01	1,879.50
Feb-01	1,901.00
Mar-01	1,925.30
Apr-01	1,914.60
May-01	1,961.50
Jun-01	1,960.60
Jul-01	1,953.40
Aug-01	1,940.20
Sep-01	1,928.00
Oct-01	1,909.20
Nov-01	1,896.40
Dec-01	1,881.40
Jan-02	1,880.20
Feb-02	1,884.00
Mar-02	1,902.60
Apr-02	1,913.40
May-02	1,937.40
Jun-02	1,990.90
Jul-02	1,994.80
Aug-02	2,013.10
Sep-02	2,002.30
Oct-02	1,982.50
Nov-02	1,969.00
Dec-02	1,959.20
Jan-03	1,928.20
Feb-03	1,952.40
Mar-03	1,980.40
Apr-03	1,972.00
May-03	1,987.80
Jun-03	2,018.70
Jul-03	2,027.80
Aug-03	2,030.20
Sep-03	2,012.20
Oct-03	2,032.30
Nov-03	2,008.30
Dec-03	2,026.80
Jan-04	1,982.30
Feb-04	1,967.20
Mar-04	1,981.60
Apr-04	1,977.40
May-04	2,020.50
Jun-04	2,074.90
Jul-04	2,069.50
Aug-04	2,064.10
Sep-04	2,050.80
Oct-04	2,057.30
Nov-04	2,037.30
Dec-04	2,056.50
Jan-05	2,017.60
Feb-05	2,030.60
Mar-05	2,039.10
Apr-05	2,051.70
May-05	2,097.70
Jun-05	2,115.90

Answer 1

Answers:

Answer a)

Months	Persons
Jan-01	1,879.50
Feb-01	1,901.00
Mar-01	1,925.30
Apr-01	1,914.60
May-01	1,961.50
Jun-01	1,960.60
Jul-01	1,953.40
Aug-01	1,940.20
Sep-01	1,928.00
Oct-01	1,909.20
Nov-01	1,896.40
Dec-01	1,881.40
Jan-02	1,880.20
Feb-02	1,884.00
Mar-02	1,902.60
Apr-02	1,913.40
May-02	1,937.40
Jun-02	1,990.90
Jul-02	1,994.80
Aug-02	2,013.10
Sep-02	2,002.30
Oct-02	1,982.50
Nov-02	1,969.00
Dec-02	1,959.20
Jan-03	1,928.20
Feb-03	1,952.40
Mar-03	1,980.40
Apr-03	1,972.00
May-03	1,987.80
Jun-03	2,018.70
Jul-03	2,027.80
Aug-03	2,030.20
Sep-03	2,012.20
Oct-03	2,032.30
Nov-03	2,008.30
Dec-03	2,026.80
Jan-04	1,982.30
Feb-04	1,967.20
Mar-04	1,981.60
Apr-04	1,977.40
May-04	2,020.50
Jun-04	2,074.90
Jul-04	2,069.50
Aug-04	2,064.10
Sep-04	2,050.80
Oct-04	2,057.30
Nov-04	2,037.30
Dec-04	2,056.50
Jan-05	2,017.60
Feb-05	2,030.60
Mar-05	2,039.10
Apr-05	2,051.70
May-05	2,097.70
Jun-05	2,115.90

Scatter of the data is as under:

Answer b)

The monthly averages (January for all years, February for all years etc.):

Month Year-01	Persons	Month Year-02	Persons	Month Year-03	Persons (Monthly Average)
Jan-01	1,879.50	Jan-02	1,880.20	Jan-03	1,879.85
Feb-01	1,901.00	Feb-02	1,884.00	Feb-03	1,892.50
Mar-01	1,925.30	Mar-02	1,902.60	Mar-03	1,913.95
Apr-01	1,914.60	Apr-02	1,913.40	Apr-03	1,914.00
May-01	1,961.50	May-02	1,937.40	May-03	1,949.45
Jun-01	1,960.60	Jun-02	1,990.90	Jun-03	1,975.75
Jul-01	1,953.40	Jul-02	1,994.80	Jul-03	1,974.10
Aug-01	1,940.20	Aug-02	2,013.10	Aug-03	1,976.65
Sep-01	1,928.00	Sep-02	2,002.30	Sep-03	1,965.15
Oct-01	1,909.20	Oct-02	1,982.50	Oct-03	1,945.85
Nov-01	1,896.40	Nov-02	1,969.00	Nov-03	1,932.70
Dec-01	1,881.40	Dec-02	1,959.20	Dec-03	1,920.30

Third year monthly average = (Month Year 01 + Month Year 02) / 2

Answer c)

There is both seasonality and trend:

As can be seen, there is cyclic changes in the monthly numbers so it is seasonal.

Also there is a trend increase from year 1 to year 2 (denoted by the straight line) so there is a trend.

Answer d)

Calculation of forecast the value for March 2020.

Yearly total for Year 2001 and Year 2002 is as under:

Year	Yearly total
Year-01	23051.1
Year-02	23429.4

Linear trend line for this forecast is :

y = 378.3x + 22673

“x” is the number of year (for year 2020, x=20)

Based on the linear trend line formula, the forecast till year 2020 is as under:

Year	Yearly total
Year-01	23051.1
Year-02	23429.4
Year-03	23807.9
Year-04	24186.2
Year-05	24564.5
Year-06	24942.8
Year-07	25321.1
Year-08	25699.4
Year-09	26077.7
Year-10	26456
Year-11	26834.3
Year-12	27212.6
Year-13	27590.9
Year-14	27969.2
Year-15	28347.5
Year-16	28725.8
Year-17	29104.1
Year-18	29482.4
Year-19	29860.7
Year-20	30239

Seasonal factor of the forecast is as under:

Month Year-01	Persons	Seaonal Factor	Month Year-02	Persons	Seaonal Factor
Jan-01	1,879.50	0.978	Jan-02	1,880.20	0.963
Feb-01	1,901.00	0.990	Feb-02	1,884.00	0.965
Mar-01 0 0 Add a comment Know the answer? Your Answer: Post as a guest Your Name: What's your source? Earn Coins Coins can be redeemed for fabulous gifts. Log In Sign Up Post as anonymous Post Your Answer Not the answer you're looking for? Ask your own homework help question Similar Questions Use the data below to answer this questions. Period Employment Jan-01 1,879.50 Feb-01 1,901.00 Mar-01 1,925.30... Use the data below to answer this questions. Period Employment Jan-01 1,879.50 Feb-01 1,901.00 Mar-01 1,925.30 Apr-01 1,914.60 May-01 1,961.50 Jun-01 1,960.60 Jul-01 1,953.40 Aug-01 1,940.20 Sep-01 1,928.00 Oct-01 1,909.20 Nov-01 1,896.40 Dec-01 1,881.40 Jan-02 1,880.20 Feb-02 1,884.00 Mar-02 1,902.60 Apr-02 1,913.40 May-02 1,937.40 Jun-02 1,990.90 Jul-02 1,994.80 Aug-02 2,013.10 Sep-02 2,002.30 Oct-02 1,982.50 Nov-02 1,969.00 Dec-02 1,959.20 Jan-03 1,928.20 Feb-03 1,952.40 Mar-03 1,980.40 Apr-03 1,972.00 May-03 1,987.80 Jun-03 2,018.70 Jul-03 2,027.80 Aug-03 2,030.20 Sep-03 2,012.20 Oct-03 2,032.30 Nov-03 2,008.30... Given the following history, use a three-quarter moving average to forecast the demand for the third... Given the following history, use a three-quarter moving average to forecast the demand for the third quarter of this year. Note, the 1st quarter is Jan, Feb, and Mar; 2nd quarter Apr, May, Jun; 3rd quarter Jul, Aug, Sep; and 4th quarter Oct, Nov, Dec. JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC     Last year 165 185 200 230 240 265 210 200 195 265 290 315   This year 175 200 165 260 260 200   Forecast... The marketing department needs to forecast the number of complaints arising from a particular defect in... The marketing department needs to forecast the number of complaints arising from a particular defect in a product. The data for several months is supplied below. Be careful since the data is listed beginning with the most recent. The forecasting method to be used here is exponential smoothing accounting for seasonality with a smoothing constant of 0.75 and a previous forecast (with seasonality) of 390. Please round your forecast to the nearest whole number. Jul 2020: 424 Jun 2020: 472... A manufacturing area needs to forecast the number of people working. The data for several months... A manufacturing area needs to forecast the number of people working. The data for several months is supplied below. Be careful since the data is listed beginning with the most recent. The forecasting method to be used here is the linear regression accounting for seasonality. Please round your forecast to the nearest whole number. ul 2020: 81 Jun 2020: 85 May 2020: 95 Apr 2020: 83 Mar 2020: 93 Feb 2020: 85 Jan 2020: 97 Dec 2019: 92 Nov 2019:... Consider a portion of monthly return data (In %) on 20-year Treasury Bonds from 2006–2010. Date... Consider a portion of monthly return data (In %) on 20-year Treasury Bonds from 2006–2010. Date Return Jan-06 5.39 Feb-06 4.83 Mar-06 5.41 Apr-06 4.64 May-06 4.05 Jun-06 3.41 Jul-06 3.92 Aug-06 3.46 Sep-06 5.06 Oct-06 5.44 Nov-06 4.96 Dec-06 4.17 Jan-07 3.48 Feb-07 4.7 Mar-07 4.38 Apr-07 3.82 May-07 4.19 Jun-07 4.35 Jul-07 3.83 Aug-07 5.42 Sep-07 3.29 Oct-07 4 Nov-07 3.42 Dec-07 3.24 Jan-08 5.21 Feb-08 4.84 Mar-08 4.59 Apr-08 3.82 May-08 3.61 Jun-08 4.34 Jul-08 4.94 Aug-08... FOR4. The Excel file Unemployment Rates provides data on monthly rates for 4 years. (8 pts)... FOR4. The Excel file Unemployment Rates provides data on monthly rates for 4 years. (8 pts) a.         Develop 3- and 6-months moving average forecasts, and exponential smoothing forecasts (use alpha of your choice) b.         Using MAD as a criterion, explain which model yields better forecast? DATA: Unemployment Rates Year Month Rate (%) 2009 Jan 7.8 2009 Feb 8.3 2009 Mar 8.7 2009 Apr 9.0 2009 May 9.4 2009 Jun 9.5 2009 Jul 9.5 2009 Aug 9.6 2009 Sep... Consider a portion of monthly return data (In %) on 20-year Treasury Bonds from 2006–2010. Date... Consider a portion of monthly return data (In %) on 20-year Treasury Bonds from 2006–2010. Date Return Jan-06 3.13 Feb-06 4.15 Mar-06 3.18 Apr-06 4.94 May-06 4.34 Jun-06 4.19 Jul-06 5.12 Aug-06 5.26 Sep-06 3.81 Oct-06 3.1 Nov-06 3.87 Dec-06 4.89 Jan-07 3.94 Feb-07 3.42 Mar-07 4.13 Apr-07 3.54 May-07 4.58 Jun-07 4.19 Jul-07 4.62 Aug-07 3.89 Sep-07 3.62 Oct-07 3.92 Nov-07 4.46 Dec-07 3.23 Jan-08 4.78 Feb-08 4.71 Mar-08 5.05 Apr-08 3.46 May-08 3.15 Jun-08 4.82 Jul-08 3.87 Aug-08... Year Month Return Year Month Return 2006     Jan 3.95 2008     Jul 3.29 2006     Feb 3.77 2008... Year Month Return Year Month Return 2006     Jan 3.95 2008     Jul 3.29 2006     Feb 3.77 2008     Aug 4.62 2006     Mar 5.29 2008     Sep 4.81 2006     Apr 3.77 2008     Oct 5.16 2006     May 4.47 2008     Nov 3.69 2006     Jun 5.2 2008     Dec 5.15 2006     Jul 3.9 2009     Jan 5.29 2006     Aug 4.33 2009     Feb 3.19 2006     Sep 4.41 2009     Mar 3.89 2006     Oct 5.14 2009     Apr 4.48 2006     Nov 3.24 2009     May 5.27 2006     Dec 4.13 2009     Jun 3.93 2007     Jan... I have the following data Week of Expenses Revenues Profit 6-Dec-04 103,084 122,533 19,449 13-Dec-04 99,584... I have the following data Week of Expenses Revenues Profit 6-Dec-04 103,084 122,533 19,449 13-Dec-04 99,584 131,036 31,452 20-Dec-04 94,936 137,813 42,877 27-Dec-04 100,757 114,495 13,738 3-Jan-05 102,736 120,579 17,843 10-Jan-05 94,866 182,122 87,256 17-Jan-05 96,158 137,983 41,825 24-Jan-05 97,013 104,668 7,655 31-Jan-05 97,796 117,807 20,011 7-Feb-05 106,315 157,735 51,420 14-Feb-05 92,307 145,685 53,378 21-Feb-05 89,923 129,758 39,835 28-Feb-05 100,546 130,642 30,096 7-Mar-05 99,270 85,895 (13,375) 14-Mar-05 98,632 125,994 27,362 21-Mar-05 100,273 113,194 12,921 28-Mar-05 100,006 127,209 27,203 4-Apr-05 105,531... A local bookstore recorded their revenue (in thousands) for the last 36 months starting in September,... A local bookstore recorded their revenue (in thousands) for the last 36 months starting in September, as provided below. a. find the deseasonalized line of best fit b. use the additive model of seasonal forecasting to predict the revenue for each month of the next academic year c. use the multiplicative model of seasonal forecasting to predict the revenue for each month of the next academic year d. what is the predicted total profit for the academic year for each... ADVERTISEMENT Need Online Homework Help? Get Answers For Free Most questions answered within 1 hours. Ask a Question ADVERTISEMENT Active Questions Assume students spend an average of $20.00 on a meal at a restaurant in 2018. Assume... asked 11 minutes ago Sixty year old Carl has just been informed that he is terminally ill. Describe how he... asked 11 minutes ago The sport of amateur boxing requires opponents to be in the same weight category to compete.... asked 11 minutes ago Randomly selected students participated in an experiment to test their ability to determine when one minute​... asked 35 minutes ago A Food Marketing Institute found that 26% of households spend more than $125 a week on... asked 37 minutes ago You normally drive on the freeway between San Diego and Los Angeles at an average speed... asked 48 minutes ago (D is a deterministic finite automata (DFA))....{<D,R>} : D is a DFA and R is a... asked 49 minutes ago 13. Enter a formula in cell M7 using the VLOOKUP function to find an exact match... asked 52 minutes ago Please Identify some of the factors related to depression in adolescents. Compare how they are the... asked 54 minutes ago A bag of Skittles is designed to have candies which contains 20% Orange. Let 1 represents... asked 1 hour ago 0. (a) Express the following statement in words: ∀n ∈ {3, 4, 5,...}, ∃a1, a2,..., an... asked 1 hour ago The velocity of propagation on a certain lossless transmission line is v=250m/µs. if C=30pF/m, find (a)... asked 1 hour ago About Contact Terms of Use Privacy Policy Academic Honesty Policy Homework Answer Scanner App Report DMCA © 2022 JustAAA   user contributions licensed under cc by-sa 4.0