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Using probability distributions for real world problems in R
By the end of this project, you will learn how to apply probability distributions to solve real world problems in R, a free, open-source program that you can download. You will learn how to answer real world problems using the following probability distributions – Binomial, Poisson, Normal, Exponential and Chi-square. You will also learn the various ways of visualizing these distributions of real world problems. By the end of this project, you will become confident in understanding commonly used probability distributions through solving practical problems and you will strengthen your core concepts of data distributions using R programming language.
These distributions are widely used in day-to-day life of statisticians for hypothesis testing and drawing conclusions on a population from a small sample. Additionally, in the field of data science, statistical inferences use probability distribution of data to analyze or predict trend from data.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Duration
3 Months
Institution
Coursera
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Coursera.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$184
Total Est. Investment
$184
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Using probability distributions for real world problems in R program at Coursera are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.