(a) (b) (c) Describe fully an appropriate dummy variable regression model to analyse the time series. Specify the assumptions involved in fitting the model and discuss how they can be checked graphically. Analyse the data fully by fitting your model (using Minitab) and interpret the results. Obtain the profit forecast for each quarter of 2023 and their 95% prediction intervals. Interpret your prediction intervals. Attach your Minitab output (at most 2 pages!) with your coursework. Explain the reasons behind autocorrelated errors in fitting regression models for time series data and the problems caused by them. Describe how they can be dealt with.
(a) (b) (c) Describe fully an appropriate dummy variable regression model to analyse the time series. Specify the assumptions involved in fitting the model and discuss how they can be checked graphically. Analyse the data fully by fitting your model (using Minitab) and interpret the results. Obtain the profit forecast for each quarter of 2023 and their 95% prediction intervals. Interpret your prediction intervals. Attach your Minitab output (at most 2 pages!) with your coursework. Explain the reasons behind autocorrelated errors in fitting regression models for time series data and the problems caused by them. Describe how they can be dealt with.
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
Related questions
Question
Y1 is 35 Y20 is 55

Transcribed Image Text:(a)
(b)
(c)
(d)
(e)
(f)
Quarterly profits, Yt, (in million £) made by a manufacturing firm for the past five years
are given in the following Table.
2019
38
INTIN
34
36
38
55
Quarter 2018
Q1
Q2
Q3
Q4
Y₁
40
2020
40
38
45
2021
41
45
46
52
53
54
Table 3: Quarterly profit in million pounds
2022
43
42
50
Y20
To analyse this data, a time series model containing trend and seasonality is proposed.
Describe fully an appropriate dummy variable regression model to analyse the time
series. Specify the assumptions involved in fitting the model and discuss how they can
be checked graphically.
Analyse the data fully by fitting your model (using Minitab) and interpret the results.
Obtain the profit forecast for each quarter of 2023 and their 95% prediction intervals.
Interpret your prediction intervals. Attach your Minitab output (at most 2 pages!) with
your coursework.
Explain the reasons behind autocorrelated errors in fitting regression models for time
series data and the problems caused by them. Describe how they can be dealt with.
Carry out the Durbin-Watson test (when your model is fitted to the above data, using
Minitab) and interpret the results. Report on your findings.
If monthly profits were available discuss how you would analyse this time series.
Discuss the appropriateness of using a Holt-Winter's method to analyse this time series
and describe in detail the model you propose for it.
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