The course will begin with what is familiar to many business managers and those who have taken the first two courses in this specialization. The first set of tools will explore data description, statistical inference, and regression. We will extend these concepts to other statistical methods used for prediction when the response variable is categorical such as win-don’t win an auction. In the next segment, students will learn about tools used for identifying important features in the dataset that can either reduce the complexity or help identify important features of the data or further help explain behavior.
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Data Modeling and Regression Analysis in Business
Université de l'Illinois à Urbana-ChampaignÀ propos de ce cours
3 512 consultations récentes
Dates limites flexibles
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Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Niveau intermédiaire
Approx. 25 heures pour terminer
Anglais
Sous-titres : Français, Portugais (européen), Russe, Anglais, Espagnol
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Niveau intermédiaire
Approx. 25 heures pour terminer
Anglais
Sous-titres : Français, Portugais (européen), Russe, Anglais, Espagnol
Offert par
Université de l'Illinois à Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
Commencez à travailler pour obtenir votre master
Ce cours fait partie du diplôme intégralement en ligne Master of Science in Accountancy (iMSA) de Université de l'Illinois à Urbana-Champaign.
Si vous êtes admis(e) au programme complet, vos cours sont pris en compte dans votre apprentissage diplômant.
Programme du cours : ce que vous apprendrez dans ce cours
8 heures pour terminer
Module 0: Get Ready & Module 1: Introduction to Analytics and Evolution of Statistical Inference
This session is an overview of the business data analytics process and its components. We introduce you to different modeling paradigms and invite you to match problems to modeling paradigms. The module concludes with an overview of Rattle (an interface for the statistical package R) and its use for univariate analysis.
8 heures pour terminer
14 vidéos (Total 93 min), 11 lectures, 3 quiz
6 heures pour terminer
Module 2: Dating with Data
This session focuses on identifying relationships between dependent and independent variables using a regression model. The goal is to find the best fitted model to the data to learn about the underlying relationship of variables in the population.
6 heures pour terminer
8 vidéos (Total 63 min), 3 lectures, 3 quiz
6 heures pour terminer
Module 3: Model Development and Testing with Holdout Data
This session introduces the student to use of a holdout data set for evaluating model performance. Methods of improving the model are discussed with emphasis on variable selection. Nuances of modeling discrete predictor variables and response variables are discussed.
6 heures pour terminer
8 vidéos (Total 66 min), 3 lectures, 4 quiz
5 heures pour terminer
Module 4: Curse of Dimensionality
There has been a tremendous increase in the way data generation via sensors, digital platforms, user-generated content, etc. are being used in the industry. For example, sensors continuously record data and store it for analysis at a later point. In the way data gets captured, there can be a lot of redundancy. With more variables, comes more trouble! There may be very little (or no) incremental information gained from these sources. This is the problem of a high number of unwanted dimensions. To avoid this pitfall, data transformation and dimension reduction comes to the rescue by examining and extracting fewer dimensions while ensuring that it conveys the full information concisely.
5 heures pour terminer
7 vidéos (Total 67 min), 3 lectures, 3 quiz
Avis
Meilleurs avis pour DATA MODELING AND REGRESSION ANALYSIS IN BUSINESS
par AS10 août 2019
The course was easy to understand and fun to practice at home which made it exciting and useful at the same time.
par BC21 août 2019
this course is easier to understand the statistical modeling, no need to learn the deep algorithm
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