Consider the following time series data. Week 1 2 3 4 5 6 Value 19 14 17 12 18 15 (a) Construct a time series plot. A time series plot contains a series of 6 points connected by line segments. The horizontal axis ranges from 0 to 7 and is labeled: Week. The vertical axis ranges from 0 to 20 and is labeled: Time Series Value. The points are plotted from left to right in regular increments of 1 week starting at week 1. The points appear to vary randomly between 10 to 17 on the vertical axis. The plot reaches its maximum time series value at week 6. A time series plot contains a series of 6 points connected by line segments. The horizontal axis ranges from 0 to 7 and is labeled: Week. The vertical axis ranges from 0 to 20 and is labeled: Time Series Value. The points are plotted from left to right in regular increments of 1 week starting at week 1. The points appear to vary randomly between 12 to 19 on the vertical axis. The plot reaches its maximum time series value at week 1. A time series plot contains a series of 6 points connected by line segments. The horizontal axis ranges from 0 to 7 and is labeled: Week. The vertical axis ranges from 0 to 20 and is labeled: Time Series Value. The points are plotted from left to right in regular increments of 1 week starting at week 1. The points appear to vary randomly between 10 to 17 on the vertical axis. The plot reaches its maximum time series value at week 1. A time series plot contains a series of 6 points connected by line segments. The horizontal axis ranges from 0 to 7 and is labeled: Week. The vertical axis ranges from 0 to 20 and is labeled: Time Series Value. The points are plotted from left to right in regular increments of 1 week starting at week 1. The points appear to vary randomly between 12 to 19 on the vertical axis. The plot reaches its maximum time series value at week 6. (b) Develop the three-week moving average forecasts for this time series. (Round your answers to two decimal places.) Week Time Series Value Forecast 1 19 2 14 3 17 4 12 5 18 6 15 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? (c) Use ? = 0.2 to compute the exponential smoothing forecasts for the time series. Week Time Series Value Forecast 1 19 2 14 3 17 4 12 5 18 6 15 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? (Round your answer to two decimal places.)

Consider the following time series data. Week 1 2 3 4 5 6 Value 19 14 17 12 18 15 (a) Construct a time series plot. A time series plot contains a series of 6 points connected by line segments. The horizontal axis ranges from 0 to 7 and is labeled: Week. The vertical axis ranges from 0 to 20 and is labeled: Time Series Value. The points are plotted from left to right in regular increments of 1 week starting at week 1. The points appear to vary randomly between 10 to 17 on the vertical axis. The plot reaches its maximum time series value at week 6. A time series plot contains a series of 6 points connected by line segments. The horizontal axis ranges from 0 to 7 and is labeled: Week. The vertical axis ranges from 0 to 20 and is labeled: Time Series Value. The points are plotted from left to right in regular increments of 1 week starting at week 1. The points appear to vary randomly between 12 to 19 on the vertical axis. The plot reaches its maximum time series value at week 1. A time series plot contains a series of 6 points connected by line segments. The horizontal axis ranges from 0 to 7 and is labeled: Week. The vertical axis ranges from 0 to 20 and is labeled: Time Series Value. The points are plotted from left to right in regular increments of 1 week starting at week 1. The points appear to vary randomly between 10 to 17 on the vertical axis. The plot reaches its maximum time series value at week 1. A time series plot contains a series of 6 points connected by line segments. The horizontal axis ranges from 0 to 7 and is labeled: Week. The vertical axis ranges from 0 to 20 and is labeled: Time Series Value. The points are plotted from left to right in regular increments of 1 week starting at week 1. The points appear to vary randomly between 12 to 19 on the vertical axis. The plot reaches its maximum time series value at week 6. (b) Develop the three-week moving average forecasts for this time series. (Round your answers to two decimal places.) Week Time Series Value Forecast 1 19 2 14 3 17 4 12 5 18 6 15 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? (c) Use ? = 0.2 to compute the exponential smoothing forecasts for the time series. Week Time Series Value Forecast 1 19 2 14 3 17 4 12 5 18 6 15 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? (Round your answer to two decimal places.)

College Algebra

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ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section4.3: Fitting Linear Models To Data

Problem 24SE: Table 6 shows the year and the number ofpeople unemployed in a particular city for several years....

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Consider the following time series data.

Week	1	2	3	4	5	6
Value	19	14	17	12	18	15

(a)

Construct a time series plot.

A time series plot contains a series of 6 points connected by line segments. The horizontal axis ranges from 0 to 7 and is labeled: Week. The vertical axis ranges from 0 to 20 and is labeled: Time Series Value. The points are plotted from left to right in regular increments of 1 week starting at week 1. The points appear to vary randomly between 10 to 17 on the vertical axis. The plot reaches its maximum time series value at week 6.

A time series plot contains a series of 6 points connected by line segments. The horizontal axis ranges from 0 to 7 and is labeled: Week. The vertical axis ranges from 0 to 20 and is labeled: Time Series Value. The points are plotted from left to right in regular increments of 1 week starting at week 1. The points appear to vary randomly between 12 to 19 on the vertical axis. The plot reaches its maximum time series value at week 1.

A time series plot contains a series of 6 points connected by line segments. The horizontal axis ranges from 0 to 7 and is labeled: Week. The vertical axis ranges from 0 to 20 and is labeled: Time Series Value. The points are plotted from left to right in regular increments of 1 week starting at week 1. The points appear to vary randomly between 12 to 19 on the vertical axis. The plot reaches its maximum time series value at week 6.

(b)

Develop the three-week moving average forecasts for this time series. (Round your answers to two decimal places.)

Week	Time Series Value	Forecast
1	19
2	14
3	17
4	12
5	18
6	15

Compute MSE. (Round your answer to two decimal places.)

MSE =

What is the forecast for week 7?

(c)

Use ? = 0.2 to compute the exponential smoothing forecasts for the time series.

Week	Time Series Value	Forecast
1	19
2	14
3	17
4	12
5	18
6	15

Compute MSE. (Round your answer to two decimal places.)

MSE =

What is the forecast for week 7? (Round your answer to two decimal places.)

(d)

Use a smoothing constant of ? = 0.4 to compute the exponential smoothing forecasts.

Week	Time Series Value	Forecast
1	19
2	14
3	17
4	12
5	18
6	15

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