How can you put data to work for you? Specifically, how can numbers in a spreadsheet tell us about present and past business activities, and how can we use them to forecast the future? The answer is in building quantitative models, and this course is designed to help you understand the fundamentals of this critical, foundational, business skill. Through a series of short lectures, demonstrations, and assignments, you’ll learn the key ideas and process of quantitative modeling so that you can begin to create your own models for your own business or enterprise. By the end of this course, you will have seen a variety of practical commonly used quantitative models as well as the building blocks that will allow you to start structuring your own models. These building blocks will be put to use in the other courses in this Specialization.
4.3 Interpretation of Regression Coefficients
Habilidades que você aprenderá
Modeling, Linear Regression, Probabilistic Models, Regression Analysis
Avaliações
JC
Feb 28, 2018
This is a good course for all of them who wish to work in this field and are unable to do so because of lack of core knowledge. The course helps to build this fundamental conceptual knowledge.
WA
Aug 30, 2017
It was a wonderful experience. The amount of knowledge have been able to acquired within the short while is quite unimaginable. I'm not the same person as at when I started the course.
This module explores regression models, which allow you to start with data and discover an underlying process. Regression models are the key tools in predictive analytics, and are also used when you have to incorporate uncertainty explicitly in the underlying data. You’ll learn more about what regression models are, what they can and cannot do, and the questions regression models can answer. You’ll examine correlation and linear association, methodology to fit the best line to the data, interpretation of regression coefficients, multiple regression, and logistic regression. You’ll also see how logistic regression will allow you to estimate probabilities of success. By the end of this module, you’ll be able to identify regression models and their key components, understand when they are used, and be able to interpret them so that you can discuss your model and convince others that your model makes sense, with the ultimate goal of implementation.
Ministrado por
Richard Waterman
Professor of Statistics
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