Descriptions
Statistician with R, master The essential Skills to get a job as a statistician! Using statistics, you can help solve real-world problems in business, engineering, science, and many other fields. In this track, you’ll learn how to use statistical methods to explore and model data, draw conclusions from a variety of data sets, and interpret and report results. statistics Is The study how to collect, analyze, and draw conclusions from data. It’s an extremely valuable tool that can help you focus on the future and derive the answer to countless questions. For example, what is the probability that someone will buy your product, how many calls will your support team receive, and how many sizes of jeans should you make to fit 95% of the population? In this course, you’ll use sales data to learn how to answer questions like these while building your statistical skills and learning how to calculate averages, use scatter plots to show the relationship between numerical values, and calculate correlations.
What you will learn
- Introduction to Statistics in R
- Basics of probability in R
- Introduction to Regression in R
- Sampling in R
- Hypothesis testing in R
- Experimental design in R
- Analyzing survey data in R
- Hierarchical and mixed-effects models in R
- Survival analysis in R
- Basics of Bayesian data analysis in R
- Factor analysis in R
Specification of the statistician with R
- Publisher : Data Camp
- Teacher: MAGGIE MATSUI
- Language: English
- Level: All levels
- Number of courses: 13
- Duration: 52 hours to complete the course
Contents of the statistician with R
Pictures
Sample clip
installation Guide
Extract the files and watch them with your favorite player
Subtitles: English
Quality: 720p
Download links
Introduction to Statistics in R
Basics of probability in R
Introduction to Regression in R
Mean regression in R
Sampling in R
Hypothesis testing in R
Experimental design in R
Analyzing survey data in R
Hierarchical and mixed-effects models in R
Survival analysis in R
Basics of Bayesian data analysis in R
Factor analysis in R
Basics of inference in R
Password file(s): free download software
File size
1.13GB