Statistics for Business Analytics: Modelling and Forecasting
The University of Queensland
This is a great course for anyone who wants to gain foundational and critical analysis and statistics skills with no prior background. In this course, we explore statistical methods for examining the relationships between variables. We also consider how data from the past can be used to make forecasts about likely future trends. We want to be able to answer questions like: What is the strength of the relationship between quality of customer experience and the likelihood of repeat purchases?...
About this Course
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.
What You'll Learn
- 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.
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.
Instructors
Temesgen Kifle
Dr