Question

In: Statistics and Probability

Intepret the time series component below with suitable sketch: 1. Seasonal component 2.cyclical component 3.irregular component...

Intepret the time series component below with suitable sketch:
1. Seasonal component
2.cyclical component
3.irregular component
4.cyclical vs seasonal
5. trend vs seasonal
6. Cyclical vs trend
7. Trend component

Solutions

Expert Solution

Time series consists of various components.

1) Seasonal component is one which repeats itself over a specific short term period such as day, month, season etc.

2) Cyclic components are long term oscillations occurring in a time series. These oscillations are mostly observed in economics data and the periods of such oscillations are generally extended from five to twelve years or more. These oscillations are associated with the well known business cycles.

3) Irregular fluctuations are sudden changes occurring in a time series which are unlikely to be repeated. They are components of a time series which cannot be explained by trends, seasonal or cyclic movements. These variations are sometimes called residual or random components. These variations, though accidental in nature, can cause a continual change in the trends, seasonal and cyclical oscillations during the forthcoming period. Floods, fires, earthquakes, revolutions, epidemics, strikes etc., are the root causes of such irregularities.

4) Cyclic vs Seasonal

A seasonal pattern exists when a series is influenced by seasonal factors (e.g., the quarter of the year, the month, or day of the week). Seasonality is always of a fixed and known period. Hence, seasonal time series are sometimes called periodic time series whereas A cyclic pattern exists when data exhibit rises and falls that are not of fixed period. The duration of these fluctuations is usually of at least 2 years. Think of business cycles which usually last several years, but where the length of the current cycle is unknown beforehand.

5) Trend vs Seasonal

The following graphs clearly explain the seasonal and trend components:

6) Cyclic vs trend

The following graphs clearly explain difference between trend and cyclic component:

7) Trend variations are those that move up or down slowly in a predictable pattern

The following graphs explain each component well:


Related Solutions

There are four components to a time series: secular trend, cyclical variation, seasonal variation, and irregular...
There are four components to a time series: secular trend, cyclical variation, seasonal variation, and irregular variation. Research these components and explain the differences as well.
2. For each, state whether the unemployment is structural, frictional, seasonal or cyclical. a. As the...
2. For each, state whether the unemployment is structural, frictional, seasonal or cyclical. a. As the United States becomes a more high-tech producer, labor-intensive factories no longer need as many workers b. Unemployment rises as output in the economy slows. c. Unemployment rate rises as the tourism months come to an end. d. As it becomes more acceptable for mothers to work, more women enter the labor market looking for work. The unemployment rate rises. e. The demand for workers...
Describe the following terms a) stationary time series b) seasonal time series c) box test (...
Describe the following terms a) stationary time series b) seasonal time series c) box test ( clearly define your notation and the null and alternative hypotheses)
1. In a time series, the component that accounts for the general movement over all the...
1. In a time series, the component that accounts for the general movement over all the years is the Group of answer choices trend cycle seasonality random error 2. If the response variable is dichotomous, one should use Group of answer choices stepwise regression best subsets regression an interaction term logistic regression 3. In a time series, predictions further in the future produce Group of answer choices narrower prediction intervals wider predication intervals 4. In a time series, moving averages...
2. Determine whether each of the following would be considered frictional, structural, seasonal, or cyclical unemployment....
2. Determine whether each of the following would be considered frictional, structural, seasonal, or cyclical unemployment. Please answer in the blank box.   A A UPS employee who was hired for the Christmas season is laid off after Christmas B A worker who is laid off due to reduced aggregate demand in the economy C A worker in a DVD rental store becomes unemployed as video-on-demand cable service becomes more popular D A new college graduate is looking for employment 3....
A technique used to isolate the trend in a time series is: adjusted factor% seasonal index...
A technique used to isolate the trend in a time series is: adjusted factor% seasonal index correction factor centered moving average seasonal decomposition
Part (A): Using R to show how to decompose the seasonal time series data and then...
Part (A): Using R to show how to decompose the seasonal time series data and then subtract that effect from the data. This assignment is to practice using R to learn how to decompose seasonal time series data. Please use the data set in “A Little of R for Time Series” Section 2.4 (p.20): • > births <-scan("http://robjhyndman.com/tsdldata/data/nybirths.dat") > birthstimeseries <-  ts(births, frequency=12, start=c(1946,1)) > birthstimeseries • Then you can use the following to show how you can decompose the time...
How would you use an error component of a time series to know if the time...
How would you use an error component of a time series to know if the time series can be used as a predictor?
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