Macquarie University
Excel Time Series Models for Business Forecasting

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Macquarie University

Excel Time Series Models for Business Forecasting

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Gain insight into a topic and learn the fundamentals.
4.9

(214 reviews)

Intermediate level
Some related experience required
11 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.9

(214 reviews)

Intermediate level
Some related experience required
11 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace

Details to know

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Assessments

19 assignments

Taught in English

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This course is part of the Excel Skills for Business Forecasting Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 6 modules in this course

Business Forecasting is part of any and every organisation. Organisations need to forecast so that they can plan for the organisation’s needs. Business forecasts are the inputs to every organisation’s planning – without business forecasts we cannot plan for our resources, our production, our supply chains – and ultimately our costs, revenues and profits. The current state of the world makes business forecasting even more fundamental to the operation of institutions. In this course we focus on Excel Skills for Business Forecasting using Time Series Models. We will be looking at how your business can utilise time series data sets to understand the different components underlying this data, and then apply the relevant model depending on these components. We will look at a range of business forecasting methods, and sometimes, more than one method may be needed! The models we look at are: Naïve Forecasting, Moving Averages, Trend-fitting, Simple Exponential Smoothing, Holt’s Exponential Smoothing, Winters Exponential Smoothing, and Decomposition. This course then continues in our second course in this specialisation which looks at Regression Models, and our third course in this specialisation which looks at Judgmental Forecasting. #EveryoneSayWow

What's included

2 videos3 readings1 discussion prompt

In this module, we explore the context and purpose of business forecasting and the three types of business forecasting — time series, regression, and judgmental. This course focuses on time series models. We will learn about time series models, as well as the component of time series data. We will then look at a preliminary forecasting method — Average Forecasts. Once we have a forecast, we need a tool to judge the accuracy of the forecasts — which are the forecasts and the error criterion calculated from these.

What's included

4 videos4 readings3 assignments

In this module, we explore different time series forecasting methods available for data that is level.

What's included

5 videos2 readings5 assignments

In this module, we explore different time series forecasting methods available for data that is trending.

What's included

4 videos3 readings3 assignments

In this module, we explore a time series forecasting method (Winters Exponential Smoothing) available for data that is seasonal.

What's included

4 videos2 readings4 assignments

In this module, we explore a time series forecasting method (Decomposition) available for data that is seasonal.

What's included

4 videos2 readings4 assignments

Instructor

Instructor ratings
4.9 (84 ratings)
Dr Prashan S. M. Karunaratne
Macquarie University
28 Courses1,358,386 learners

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4.9

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