The objective of this course is to provide an understanding for the Data Science students on statistical concepts to include sampling, estimation using confidence intervals, hypothesis testing, regression, correlation analysis, Goodness-of-fit tests and independence Chi square tests. By completing this course the student will learn to perform the following: 1) How to calculate and apply measures of location and measures of dispersion using R language. 2) How to apply discrete and continuous probability distributions to various data analysis problems using R language. 3) Perform Test of Hypothesis as well as calculate confidence interval for a population parameter for single sample and two sample cases. Understand the concept of p-values. 4) Learn non-parametric test such as the Chi-Square test for Independence as well as Goodness of Fit. 5) Compute and interpret the results of Bivariate Regression and Correlation Analysis, for forecasting. Furthermore, being able to perform these studies using R language.

Temps présentiel : 37.5 heures

Charge de travail étudiant : 150 heures

Méthode(s) d'évaluation : Evaluation - Examen final, Evaluation - Examen partiel

Référence :
A Handbook of Statistical Analyses Using R, Brian S. Everitt and Torsten Hothorn Probability and Statistics for Engineers and Scientists, Walpole and Myers.