![excel linear regression plot excel linear regression plot](https://i1.wp.com/shoutingdata.com/wp-content/uploads/2020/07/Slide1-4.jpg)
The course provides a combination of conceptual and hands-on learning. This is an introductory course to predictive modeling. Use Excel to prepare data for predictive modeling, including exploring data patterns, transforming data, and dealing with missing values. Understand different types of data and how they may be used in predictive models. Be able to fit several time-series-forecasting models (e.g., exponential smoothing and Holt-Winter’s method) in Excel, evaluate the goodness of fit, and use fitted models to make forecasts.
#EXCEL LINEAR REGRESSION PLOT SERIES#
Understand the concepts, processes, and applications of time series forecasting as a special type of predictive modeling. Understand the problem of overfitting and underfitting and be able to conduct simple model selection. Be able to fit simple and multiple linear regression models to data, interpret the results, evaluate the goodness of fit, and use fitted models to make predictions.
![excel linear regression plot excel linear regression plot](https://engineerexcel.com/wp-content/uploads/2016/02/022316_2016_LinearRegre3.png)
Understand the structure of and intuition behind linear regression models. Understand the concepts, processes, and applications of predictive modeling. By the end of the course, you will be able to: This course will introduce to you the concepts, processes, and applications of predictive modeling, with a focus on linear regression and time series forecasting models and their practical use in Microsoft Excel.
![excel linear regression plot excel linear regression plot](https://www.free-online-converters.com/blog/2020/07/3085-1.jpg)
Welcome to Introduction to Predictive Modeling, the first course in the University of Minnesota’s Analytics for Decision Making specialization.