Statistics for Business Analytics 3: Modelling and Forecasting
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.Created by: The University of Queensland
Level: Introductory
Related Online Courses
The R language plays a critical role in data analysis and a common programming language when working in the field of data science & analytics. This course will introduce you to R language... more
Probability and statistics help to bring logic to a world replete with randomness and uncertainty. This course will give you tools needed to understand data, science, philosophy, engineering,... more
El futuro pertenece a la ciencia de datos y a quienes la entiendan. Al igual que el petróleo y el gas impulsaron las economías de los siglos XX y XXI, los datos impulsan cada vez mas la i... more
The R programming language is purpose-built for data analysis. R is the key that opens the door between the problems you want to solve with data and the answers you need to meet your objectives.... more
Demystify complex big data technologies Compared to traditional data processing, modern tools can be complex to grasp. Before we can use these tools effectively, we need to know how to handle big... more
Powered by
