This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The concepts and techniques in this course will serve as building blocks for the inference and modeling courses in the Specialization.
Normal Distribution
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Habilidades que você aprenderá
Statistics, R Programming, Rstudio, Exploratory Data Analysis
Avaliações
4.7 (5,244 classificações)
- 5 stars78,29%
- 4 stars17,35%
- 3 stars2,44%
- 2 stars0,64%
- 1 star1,25%
AA
23 de jan de 2018
This course literally taught me a lot, the concepts were beautifully explained but the way it was delivered and overall exercises and the difficulty of problems made it more challenging and enjoying.
BB
3 de set de 2019
Very clearly explained and the pace is awesome! I really enjoy each deadline and l can already see how it is impacting my day to day work and life. I ook forward to completing the course! Thank you.
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Probability Distributions
Great work so far! Welcome to Week 4 -- the last content week of Introduction to Probability and Data! This week we will introduce two probability distributions: the normal and the binomial distributions in particular. As usual, you can evaluate your knowledge in this week's quiz. There will be no labs for this week. Please don't hesitate to post any questions, discussions and related topics on this week's forum (https://www.coursera.org/learn/probability-intro/module/VdVNg/discussions?sort=lastActivityAtDesc&page=1). Also this week, you will be asked to complete an initial data analysis project with a real-world data set. The project is designed to help you discover and explore research questions of your own, using real data and statistical methods we learn in this class. Please read the project instructions to complete this self-assessment.
Ministrado por
Mine Çetinkaya-Rundel
Associate Professor of the Practice
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