Data

All 90 data sets from the book are avail­able below. These include examples in the text as well as data sets used in the exer­cises. Just click on the line and save the file. They are stored as csv files and should be able to be read by MS-Excel, any text editor and any fore­cast­ing or stat­ist­ical package.

Altern­at­ively, you can down­load all files as a ZIP file. (You may need Win­Zip.)

For users of R, all data sets are avail­able ready to use in the fma pack­age.

For users of RATS, data and code are avail­able for the examples in the book. These are also included on the CD with the cur­rent release of the RATS software.

Over 800 other time series are avail­able in the Time Series Data Lib­rary along with the 3003 series from the M3-Competition.

Chapter 1: The fore­cast­ing perspective.

• Aus­tralian monthly elec­tri­city production
• US Treas­ury bill contracts
• Sales of product C
• Aus­tralian clay brick production

Chapter 2: Basic fore­cast­ing tools.

• Price, mileage and coun­try of ori­gin for 45 auto­mo­biles from Con­sumer Reports,
  April 1990, pp.235–255.
• Monthly Aus­tralian beer pro­duc­tion: Jan 1991 — Aug 1995
• Expendit­ures for 12 super­mar­ket customers.
• Aus­tralian monthly elec­tri­city production
• Monthly milk pro­duc­tion per cow over 14 years
• Exer­cise 2.1:Aver­age monthly tem­per­at­ure in Paris.
• Exer­cise 2.3:
  • Monthly total of people on unem­ployed bene­fits in Aus­tralia (Jan 1956 — Jul 1992)
  • Daily morn­ing tem­per­at­ure of a cow. Meas­ure at 6.30am each morn­ing by count­ing chirps from a tele­met­ric ther­mo­meter implanted in the cow. Data are chirps per 5-minute inter­val minus 800. Source: The ABC of EDA by Paul Velle­man (1981) Duxbury Press.
  • Annual num­ber of lynx trapped in McK­en­zie River dis­trict of north­w­est Canada (1821–1934).
  • Acci­dental deaths in USA (monthly)
  • Aus­tralian clay brick production
• Exer­cise 2.4:
  • Daily morn­ing tem­per­at­ure of a cow. See Ex 2.3 for details.
  • Acci­dental deaths in USA (monthly)
  • Inter­na­tional air­line pas­sen­gers (1949–1956)
  • Annual num­ber of minks trapped in McK­en­zie River dis­trict of north-west Canada (1848–1911)
• Exer­cise 2.5: Run­ning times and max­imal aer­obic capa­city for 14 female runners.
• Exer­cise 2.6: Demand and fore­casts for product E15.
• Exer­cise 2.7: Dow Jones index, 28 Aug — 18 Dec 1972.
• Exer­cise 2.8: Japan­ese motor vehicle pro­duc­tion (1947–1989) in thousands.

Chapter 3: Time series decomposition.

• Monthly sales of new one-family houses sold in the USA since 1973.
• Sales of sham­poo over a three year period
• Monthly inter­na­tional air­line pas­sen­ger traffic from 1949–1956.
• Exer­cise 3.1: ship­ments.
• Exer­cise 3.4: quarterly elec­tri­city production.
• Exer­cise 3.5: Monthly sales of product A for a plastics manufacturer
• Exer­cise 3.7: Quarterly reports of a French company
• Exer­cise 3.8: Num­ber of per­sons in the civil­ian labour force in Aus­tralia each month from Feb 1978 — Aug 1995

Chapter 4: Expo­nen­tial smooth­ing methods.

• Elec­tric can opener shipments
• Invent­ory demand for product E15
• Quarterly sales data
• Exer­cise 4.1: Cana­dian unem­ploy­ment rate as a per­cent­age of the civil­ian labor force between 1974 and the third quarter of 1975
• Exer­cise 4.2: Sales of elec­tric knives for the period Jan 1991 through April 1992
• Exer­cise 4.4: French index of industry
• Exer­cise 4.5: Daily sales of paper­back and hard­cover books
• Exer­cise 4.6: Elec­tric can opener shipments
• Exer­cise 4.7: Monthly inter­na­tional air­line pas­sen­ger traffic from 1949–1956.
• Exer­cise 4.8: Quarterly sales data

Chapter 5: Simple regression.

• Sales data over 10 time peri­ods.World pulp prices and shipments
• “King Kong” data
• GDP for West­ern Europe and PCV industry sales
• Exer­cise 5.2: Costs and units produced.
• Exer­cise 5.3: Ozone deple­tion and melan­oma rates.
• Exer­cise 5.4: Scores on manual dex­ter­ity test and pro­duc­tion rat­ings for 20 workers
• Exer­cise 5.5: Elec­tri­city con­sump­tion and maxium tem­per­at­ures for 12 ran­domly chosen days
• Exer­cise 5.6: “King Kong” data
• Exer­cise 5.7: Win­ning times for the men’s 400 m final in each Olympic Games from 1896 to 1996.
• Exer­cise 5.8: Monthly sales for a souvenir shop on the wharf at a beach resort town in Queens­land, Australia.
• Exer­cise 5.9: Mor­tal­ity data for 156 poultry farms, Aug 95-Jul 96.
• Exer­cise 5.10: Price and per cap­ita con­sump­tion of nat­ural gas in 20 towns in Texas

Chapter 6: Multiple regression.

• Bank data
• Three sets of resid­uals (Fig­ure 6–6).
• Exer­cise 6.2: Price and per cap­ita con­sump­tion of nat­ural gas in 20 towns in Texas
• Exer­cise 6.4: Cement com­pos­i­tion and heat data.
• Exer­cise 6.5: Monthly dol­lar volume of sales on Boston stock exchange and com­bined New York and Amer­ican stock exchanges
• Exer­cise 6.7: Sales and advert­ising expendit­ure for an auto­mot­ive parts company.

Chapter 7: The Box-Jenkins meth­od­o­logy for ARIMA models.

• Time series with 36 values
• Monthly total num­ber of pigs slaughtered in the state of Vic­toria, Aus­tralia,
  from Janu­ary 1990 through August 1995
• Dow-Jones index on 251 trad­ing days end­ing 26 August 1994
• Aus­tralian Monthly elec­tri­city pro­duc­tion data from Janu­ary 1980 to August
  1995
• Num­ber of users logged on to an Inter­net server each minute over 100
  minutes
• Industry sales for print­ing and writ­ing paper (in Thou­sands of french francs).
  Janu­ary 1963 — Decem­ber 1972
• Monthly ship­ment of pol­lu­tion equip­ment from Jan. 1966 through Dec. 1975 (in
  thou­sands of french francs)
• Exer­cise 7.2: Daily clos­ing IBM stock prices
• Exer­cise 7.3: White noise series.
• Exer­cise 7.4: Num­ber of strikes in the US from 1951 to 1980.
• Exer­cise 7.5: Stocks of evap­or­ated and sweetened con­densed milk
• Exer­cise 7.6: Sheep pop­u­la­tion (in mil­lions) of Eng­land and Wales from 1867 — 1939
• Exer­cise 7.7: Annual bitu­min­ous coal pro­duc­tion in the USA from 1920 — 1968
• Exer­cise 7.8: The total gen­er­a­tion of elec­tri­city by the U.S. elec­tric industry (monthly data for the period Jan. 1985 — Oct. 1996) For recent data, click here
• Exer­cise 7.9: Employ­ment fig­ures in the motion pic­ture industry (SIC Code 78) for the period Jan. 1955 through Dec. 1970
• Exer­cise 7.10: Sales of new one-family houses, USA, from Jan 1987 through Nov 1995

Chapter 8: Advanced fore­cast­ing models.

• Japan­ese motor vehicle pro­duc­tion (1947–1989) in thousands.
• US monthly sales of pet­ro­leum and related products. Jan 1971 — Dec 1991.
• Sales volume and advert­ising expendit­ure for a diet­ary weight con­trol
  product.
• Monthly hous­ing starts, con­struc­tion con­tracts and aver­age new home mort­g­ate
  rates. Jan 83 — Oct 89.
• Monthly total deaths and ser­i­ous injur­ies on UK roads. Jan 75 — Dec 84.
• Sea­son­ally adjus­ted quarterly cap­ital expendit­ure and appro­pri­ations in U.S.
  man­u­fac­tur­ing, 1953–1974.
• Exer­cise 8.1: Sales and advert­ising expendit­ure for an auto­mot­ive parts company.
• Exer­cise 8.2: Level of Lake Huron in feet (reduced by 570 feet), 1875 — 1972.
• Exer­cise 8.6: Input series.
• Exer­cise 8.7:
  • Total room nights occu­pied and total monthly tak­ings from accom­mod­a­tion at hotels, mos­tels, and guest houses in Vic­toria, Aus­tralia. Jan 80 — Jun 95.
  • Quarterly CPI (con­sumer price index) for Vic­toria. Q1 1980 — Q2 1995.
• Exer­cise 8.8: Daily per­cep­tual speed scores for a schizo­phrenic patient. A new drug was intro­duced on day 61.

Chapter 9: Fore­cast­ing the long term

• Fig 9–1: Monthly cop­per prices for 28 con­sec­ut­ive months
• Fig 9–2: Yearly cop­per prices for 14 con­sec­ut­ive years
• Fig 9–3: Yearly cop­per prices for 43 con­sec­ut­ive years
• Fig 9–4: Yearly cop­per prices, 1800–1997 (1997 dollars)
• Fig 9–5: IBM sales and profits (1954–1984) and forecasts.
• Fig 9–6: Wheat prices, 1264–1996, in con­stant 1996 pounds.
• Fig 9-7a: Nail prices, 1800–1996, in constant $.
• Fig 9-7b: Price of chicken, 1924–1993, in constant $.
• Fig 9-7c: Price of a dozen eggs, 1900–1993, in constant $.
• Fig 9-7d: Tele­phone cost: New York — San Fran­cisco. 1915 — 1996
• Fig 9–8: Real daily wages in pounds, Eng­land. 1260 — 1994
• Fig 9-9a: Annual Cop­per prices, 1800–1997
• Fig 9-9b: Quarterly S&P 500 index, 1900–1996

Chapter 10: Judg­mental fore­cast­ing and adjustments.

• Fig 10–4: Sales of Elco’s laser print­ers: 1992–1998.
• Fig 10–6: Oil prices in con­stant 1997 dol­lars. 1870–1997.

Chapter 11: The use of fore­cast­ing meth­ods in practice.

• Fig 11–2: example of combining

Chapter 12: Imple­ment­ing fore­cast­ing: its uses, advant­ages and limitations.

No data