Compare the accuracy of the techniques using rmse

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Reference no: EM133903124 , Length: word count:500

Data-driven Forecasting

Assessment - A Forecasting Project

Task
Apply forecasting techniques to a given dataset and provide a business application of the forecasts. The assessment is worth 30 marks (see rubric for allocating these marks).

Assessment Description
You will be provided with a dataset on the day of the assessment.
The data provided for the assessment are a time series of monthly sales revenue for a company.
The objective of the assessment is to use software to:
describe the time series, develop a sales forecast model.

Assessment Instructions

In class: You will be presented with a dataset in class. As a group, analyse the dataset. Present your work as a group during the third hour of the workshop.

As a group:
You will be provided with a dynamic dataset on the day of the assessment.
Case Study: Sales Forecasting for NovaTech Electronics

Background:
NovaTech Electronics is a growing retailer specialising in smart home devices. The company has collected monthly sales data for eight years (synthesised data provided) and wants to improve its forecasting accuracy to optimise inventory and marketing strategies. Your group must develop a forecast model and present a data-driven decision-making strategy. Access assignment help for any subject instantly.

Task:
Your group will apply forecasting techniques to the provided dataset and deliver a presentation
outlining your approach, findings, and recommendations.
Data Analysis (100 words maximum)
Explore the dataset and summarise key insights.
Identify potential trends, seasonality, and irregular patterns.
Visualise the data using appropriate graphs.

Forecasting Application ( 50 words maximum)
Apply two forecasting techniques for sales using a software of your choice
Compare the accuracy of the techniques using RMSE.
Justify your model choice based on evidence.

Recommendations for Decision-Making ( 100 words maximum)
Interpret the results in a business context.
Provide a forecast-driven strategy for inventory and marketing planning.

Presentation
Each group will deliver a 5-8-minute presentation explaining their methodology, findings,
and recommendations in class in the final hour.
The presentation (about 8 to 12 slides including cover and references) should be well- structured, engaging, and include visualisations and data interpretations.

Task:
Forecasting Application ( 100 words maximum)
Use the dynamic dataset provided and refresh to have a different realisation of the data for your individual report (which should be different from that used for the group exercise). Fit Prophet to the time series using both additive and multiplicative seasonal models.
State which of the additive or seasonal model is better and give a reason for this preference. State the January seasonal effect for your preferred model (as either a monthly additive effect or a monthly index).
Plot the data and fitted Prophet model for your preferred seasonal model, together with forecasts for 12 months ahead.

Reflection on Data-Driven Decision-Making in context ( 150 words maximum)
Discuss qualitative and quantitative forecasting techniques in the context of this application.
Reflect on how your forecasting results can impact real-world business decisions in this application.

Reference no: EM133903124

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