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.

• 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.