Question 1

Which of the four time series components is more likely to exhibit the relative steady growth of the population of Las Vegas from 1964 to 2004?

Accepted Answer

The long-term trend component of a time series represents the gradual growth or decline of the data over a long period of time. Population growth over a span of forty years is likely to exhibit a relative steady growth, which is best represented by the long-term trend component.

Question 2

We compute the five-period moving averages for all time periods except the first two and last two time periods.

Accepted Answer

The question states that we exclude the first two and last two time periods, so we can only compute the five-period moving averages for the remaining time periods.

Question 3

The time series component that reflects a long-term,relatively smooth pattern or direction exhibited by a time series over a long time period (more than one year)is called:

Accepted Answer

Long-term trend is the component of a time series that reflects a long-term, relatively smooth pattern or direction exhibited by a time series over a long time period (more than one year). It can be increasing, decreasing or remain constant over time.

Question 4

The time series component that reflects the irregular changes in a time series that are not caused by any other component,and tends to hide the existence of the other more predictable components,is called:

Accepted Answer

The random variation is also known as the residual component, which represents the unpredictable and irregular part of a time series that cannot be explained by any other component. It tends to obscure the underlying patterns and relationships within the data, making it difficult to identify the other more predictable components such as trend, seasonality, and cycle. Therefore, option D - random variation is the correct answer.

Question 5

We compute the three-period moving averages for all time periods except the first and the last.

Accepted Answer

The statement is true as three-period moving averages require a minimum of three periods of data to calculate an average, hence the first and last periods cannot have a three-period moving average.

Question 6

The principle of parsimony indicates that the simplest model that gets the job done adequately should be used.

Accepted Answer

The principle of parsimony, also known as Occam's Razor, states that the simplest explanation that adequately explains a phenomenon should be preferred over more complex explanations. This principle is commonly used in scientific and logical reasoning.

Question 7

The time series component that reflects a wavelike pattern describing a long-term trend that is generally apparent over a number of years is called:

Accepted Answer

Cyclical variation is the time series component that reflects a wavelike pattern describing a long-term trend that is generally apparent over a number of years. This can be caused by economic cycles, political cycles, or other large-scale societal changes that lead to fluctuations in the data. The other answer choices refer to different time series components: long-term trend refers to a gradual change in the mean level of the data over time, seasonal variation refers to recurring patterns that occur within a year, and random variation refers to the unpredictable, erratic variability in the data that cannot be explained by other factors.

Question 8

Each forecast using the method of exponential smoothing depends on all the previous observations in the time series.

Accepted Answer

Exponential smoothing is a method that assigns exponentially decreasing weights to the past observations in a time series, with the most recent observations weighted more heavily. Therefore, each forecast is dependent on all previous observations in the series.

Question 9

Smoothing time series data by the moving average method or exponential smoothing method is an attempt to remove the effect of the random variation component.

Accepted Answer

Smoothing methods aim to remove the effect of random variation or noise in time series data. Both moving average and exponential smoothing methods can be used for this purpose.

Question 10

The term "seasonal variation" may refer to:

Accepted Answer

Seasonal variation refers to systematic patterns or changes that occur at specific regular intervals, such as daily, weekly, or across the four traditional seasons, affecting data or phenomena being observed.

Question 11

Given a data set with 15 yearly observations,a 3-year moving average will have fewer observations than a 5-year moving average.

Accepted Answer

A 3-year moving average will have more observations than a 5-year moving average because it requires fewer years of data to calculate each point, thus starting and ending closer to the dataset's boundaries.

Question 12

A trend is a persistent pattern in annual time-series data that has to be followed for several years.

Accepted Answer

A trend is a long-term pattern in the data that persists over time. It is characterized by a general direction in which the data points are moving.

Question 13

A time series is:

Accepted Answer

A time series is a set of measurements on a variable taken over some time period in sequential order. It involves analyzing patterns and forecasting future values based on past trends. Option A describes cross-sectional data, while options C and D refer to regression models and forecasting models, respectively, which may use time series data as input.

Question 14

The time series component that reflects variability over short repetitive time periods and has duration of less than one year is called:

Accepted Answer

Seasonal variation reflects fluctuations that occur in a cyclic pattern over a period of less than one year, such as monthly or quarterly fluctuations. Long-term trend reflects the underlying direction in which a variable is moving over the long term, and cyclical variation reflects fluctuations that occur in a cyclic pattern over a period of more than one year. Random variation reflects fluctuations that cannot be attributed to any identifiable cause or pattern.

Question 15

The seasonal variation,one of the four different components of a time series,is more likely to exhibit the relatively steady growth of the population of the United States from 181 million in 1960 to 273 million in 1999.

Accepted Answer

The seasonal variation component of a time series refers to periodic fluctuations that occur at regular intervals such as weekly, monthly or quarterly. It is unlikely to exhibit the steady growth of a population over a period of 39 years.

Question 16

If a time series does not exhibit a long-term trend,the method of exponential smoothing may be used to obtain short-term predictions about the future.

Accepted Answer

Exponential smoothing is a forecasting technique that is commonly used for time series data. It works by giving more weight to recent observations and less weight to older observations in a weighted moving average. It is particularly useful for short-term predictions when the data does not exhibit a long-term trend.

Question 17

A time series can consist of four different components: long-term trend,cyclical variation,seasonal variation,and random variation.

Accepted Answer

A time series can consist of these four components: long-term trend (overall upward or downward movement), cyclical variation (regular patterns of highs and lows that last for more than one year), seasonal variation (regular patterns that repeat within a year, such as higher sales in the summer months), and random variation (unpredictable fluctuations that do not follow a pattern or trend).

Question 18

Cyclical variation,one of the four different components of a time series,is more likely to exhibit business cycles that record periods of economic recession and inflation.

Accepted Answer

Cyclical variation, also known as business cycle, is the component of a time series that shows the regular pattern of expansion and contraction in economic activity, such as periods of economic recessions and inflation. Therefore, it is more likely to exhibit business cycles.

Question 19

Which of the four-time series component is more likely to exhibit the changes in stock market prices at particular times during the course of one day?

Accepted Answer

The answer of Which of the four-time series component is...

Question 20

We calculate the three-period moving averages for a time series for all time periods except the:

Accepted Answer

The three-period moving average requires three consecutive periods to calculate an average. Therefore, we cannot calculate the moving average for the first two periods and the last two periods since we do not have three consecutive values before or after them. Hence, the best choice is to exclude the first and last period, as we need at least one period before and after to compute the moving average.

Quiz 20: Time-Series Analytics and Forecasting