Course description
Statistics for Business Analytics: Modelling and Forecasting
We consider questions like these across three topics:
- Topic 1 starts with simple, familiar ideas like correlation and builds on these to consider how simple linear regression can be applied to quantify the relationships between variables.
- Topic 2 examines multiple linear regression and considers how we can establish models that allow us to predict values for variables of interest in circumstances where there are many variables at work.
- Topic 3 considers the details of time series forecasting , using different methods of trend fitting to make predictions about future data.
Who should attend?
Prerequisites
This is an Introductory level course, with no prior knowledge in statistics required. Only a basic level of junior high school math is assumed.
Course delivery details
This course is offered through The University of Queensland, a partner institute of EdX.
4-8 hours per week
Costs
- Verified Track -$149
- Audit Track - Free
Certification / Credits
What you'll learn
Upon successful completion of this course, you will be able to:
- Interpret the different components of a linear regression equation.
- Distinguish between statistical measurements such as R, R2 and adjusted R2 to assess goodness-of-fit for a regression model.
- Use technological tools to construct simple and multiple linear regression models.
- Describe the components of a time series.
- Select from a range of different methods to determine the most appropriate choice for trend fitting and forecasting for a given set of time series data.
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edX
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