COMM 395:
COURSE PROJECT
This assessment takes the form of an essay along with class presentation and accounts for 20% of your total mark and the deadline for submission is on 28 march 2024 by 11:59pm.
The Task
The objective of this coursework is to go through forecasting steps and propose and build a framework to forecast daily and monthly time series of the given dataset.
Figure 1: process of producing forecasts for time series data
Once you prepare your data for forecasting and conduct a preliminary analysis to determine whether they contain any key feature (Part A), then you need to identify suitable forecasting models (Part B), specify and train models on your data (Part C), check the validity of your model and evaluate its point and interval forecast accuracy and use the most accurate model to forecast the future (Part D).
Submission format
You should submit, a Zip file containing your report in a Pdf format and your R code.
Data
The dataset is provided in a CSV file. The dataset chosen for this assessment is the sales of 40 products from a retailer.
It contains multiple variables.
item_id
dep_id
store_id
state_id
month
sales
Part A: prepare data and visualise.
Once you have the data, you can start by importing them into R. you need to make sure your data is a quality data and if required you need to clean data, remove duplication, deal with explicit and implicit missing values.
You need to create suitable graphs to identify key features of your data. You need to describe and interpret key features available in your data.
Part B: Select a suitable toolbox of forecasting models.
Your toolbox should contain:
exponential smoothing models
arima models
regression model
A simple benchmark method
The selected models should be able to capture collectively different underlying time series characteristics of data (level, trend, seasonality, autocorrelation). You need to describe the models in the report. A full justification of the selected models should be provided.
Part C: Train models on your data and forecast.
In this part, you need to specify models discussed in Part B and train them on your data.
Forecast sales for 6 months ahead.
Part D: Model performance evaluation
You need to select a strategy to decide which forecasting model is the most accurate one. Evaluate the forecasts produced using at least three appropriate point error measures and one interval accuracy measure and one distributional accuracy measure. Compare the forecast accuracy measures. Which model do you select as the most accurate model to suggest it to the decision maker for use in the future?
Perform residual diagnostics for the most accurate model. What does the residual diagnostics tell you?
Please note that in all the above parts the quality of presentation, critical discussion and appropriate references to the literature will be taken explicitly into account towards the mark to be allocated. You need to use R software to do all analysis, any other tools such as Excel is not allowed.
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The essay should be NO MORE THAN 3,000 WORDS IN LENGTH and all sources should be acknowledged in the appropriate place in the text. You are advised to use the Harvard referencing system. References are excluded from world count.
Unfair Practice
This is an individual assignment and you are advised not to engage in any activity that might lead to suspicions of Unfair Practice.
Course Project marking-criteria
For 90%+
An outstanding piece of work, showing mastery of the subject matter, with a highly developed ability to analyse, synthesise and apply knowledge and concepts. All objectives of the assignment are covered, and the work is free of error with very high level of technical competence. There is evidence of critical reflection; and the work demonstrates originality of thought, and the ability to tackle questions and issues not previously encountered. Ideas are expressed with fluency. All coursework requirements are met and exceeded.
For 70% – 89%
An excellent piece of work, showing a high degree of mastery of the subject matter, with a well-developed ability to analyse, synthesise and apply knowledge and concepts. All major objectives of the set work are covered, and work is free of all but very minor errors, with a high level of technical competence. There is evidence of critical reflection, and of ability to tackle questions and issues not previously encountered. Ideas are expressed clearly. However, the originality required for a 90+ mark is absent. All coursework requirements are met and some are exceeded.
For 60%-69%
A very good piece of work, showing a sound and thorough grasp of the subject-matter, though lacking the breadth and depth required for a first-class mark. A good attempt at analysis, synthesis and application of knowledge and concepts, but more limited in scope than that required for a mark of 70+. Most objectives of the work set are covered. Work is generally technically competent, but there may be a few gaps leading to some errors. Some evidence of critical reflection, and the ability to make a reasonable attempt at tackling questions and issues not previously encountered. Ideas are generally expressed with clarity, with some minor exceptions. All coursework requirements are addressed adequately.
For 50%-59%
A fair piece of work, showing grasp of major elements of the subject-matter but possibly with some gaps or areas of confusion. Only the basic requirements of the work are covered. The attempt at analysis, synthesis and application of knowledge and concepts is superficial, with a heavy reliance on course materials. Work may contain some errors, and technical competence is at a routine level only. Ability to tackle questions and issues not previously encountered is limited. Little critical reflection. Some confusion and immaturity in expression of ideas. Most coursework requirements are addressed.
For 40%-49%
A poor piece of work, showing some familiarity with the subject matter, but with major gaps and serious misconceptions. Only some of the basic requirements of the work set are achieved. Little or no attempt at analysis, synthesis or application of knowledge, and a low level of technical competence, with many errors. Difficulty in beginning to address questions and issues not previously encountered. Some intended learning outcomes are achieved.
For 30%-39%
Work not of passable standard, with serious gaps in knowledge of the subject matter, and many areas of confusion. Few or none of the basic requirements of the work set are achieved, and there is an inability to apply knowledge. Technical competence is poor, with many serious errors. The student finds it difficult to begin to address questions and issues not previously encountered. The level of expression and structure is very inadequate. Few intended learning outcomes are achieved.
Below 30%
A very poor piece of work, showing that the student has failed to engage seriously with any of the subject matter involved, and/or demonstrates total confusion over the requirements of the work set. Virtually none of the intended learning outcomes are achieved.
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