Which of the following cant be a component for a time series plot seasonality trend cyclical none of the above?

Time Series is a time ordered collection of data points. The observations are taken at a predefined interval of time (may be seconds, minutes, hours, days, weeks etc.). Time series analysis is the study of the ordered data points to extract meaningful insights and its other characteristics. It has the following components
 

Trends: A long term pattern of the time series. It may exhibit an increasing or decreasing trend
Cyclical: A pattern showing a continuous up and down movement
Seasonal: A regular fluctuation during the same time of the year which repeats year after year

An application-oriented question on the topic along with responses can be seen below. The best answer was provided by Sandip Mittra on 10th Dec 2021.

Applause for all the respondents - James Bob Lawless, Manas Mohapatra, C V Satish, Mohit Kumar, Gaurav Mathur, Parthasarathy Raghava, Gopal Menon, Sandip Mittra, Johanan Collins.

2. Which of the following can’t be a component for a time seriesplot?A) SeasonalityB) TrendC) CyclicalD) NoiseE)None of the above

Activity 13. A pattern that is repeated throughout a time series and has a recurrenceperiod of at most one year is called:

Get answer to your question and much more

4. In time series seasonal variations can occur within a period of:

Get answer to your question and much more

Activity 15. The rise and fall of a time series over periods longer than oneyear is called:

Get answer to your question and much more

6. A time series has:(a) Two components(b) Three components(c)Four components(d) Five components

Time Series: Stationary ModelsStationary Model AssumptionsAssumes item forecasted will stay steady over time(constant mean; random variation only)Techniques will smooth out short-term irregularitiesThe forecast is revised only when new data becomesavailable.Stationary Model TypesNaïve ForecastMoving Average/Weighted Moving AverageExponential Smoothing

14Stationary data forecastingNaïveI sold 10 units yesterday, so I think I will sell 10units today.n-period Moving AverageFor the past n days, I sold 12 units on average.Therefore, I think I will sell 12 units today.Exponential smoothingI predicted to sell 10 units at the beginning ofyesterday; At the end of yesterday, I found out Isold in fact 8 units. So, I will adjust the forecast of10 (yesterday’s forecast) by adding adjusted error(α * error). This will compensate over (under)forecast of yesterday.

15Naïve ModelThe simplest time series forecasting modelIdea: “what happened last time period (lastyear, last month, yesterday) will happenagain this time”Naïve Model:Algebraic:Ft= Yt-1Yt-1: actual value in period t-1Ft: forecast for period tSpreadsheet: B3:= A2; Copy down

18Moving Average ModelSimple n-Period Moving AverageIssues of MA ModelNaïve model is a special case of MA with n = 1Idea is to reduce random variation or smooth dataAll previous n observations are treated equally (equalweights)Suitable for relatively stable time series with no trend orseasonal patternnYYnTTitt1nntY2tY1tYˆ=tFnperiodsnpreviousinvaluesactualofSumˆtF

Example: Weekly Department Store SalesThe weekly salesfigures (in millions ofdollars) presented inthe following table areused by a majordepartment store todetermine the need fortemporary salespersonnel.Period (t)Sales (y)15.324.435.445.855.664.875.685.695.4106.5115.1125.8135146.2155.6166.7175.2185.5195.8205.1215.8226.7235.2246255.8

Example: Weekly Department Store SalesUse a three-week moving average (k=3) forthe department store sales to forecast for theweek 24 and 26.

Upload your study docs or become a

Course Hero member to access this document

Upload your study docs or become a

Course Hero member to access this document

End of preview. Want to read all 74 pages?

Upload your study docs or become a

Course Hero member to access this document

Which is not a component of time series?

What are the 4 components of time series?

Which of the following can be component for a time series plot?

Which of the following is not an example of a time series model?