Statistician in R

Diperbarui 03/2025

A statistician collects and analyzes data and helps companies make sense of quantitative data, including spotting trends and making predictions.

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Deskripsi Lagu

Statistician in R

Unlock the Power of Statistics with R

Become a statistician and help solve real-world problems across industries by mastering statistical methods and tools in R. In this Track, you'll learn how to collect, analyze, and draw accurate conclusions from a wide variety of datasets. Gain hands-on experience in exploring and modeling data, interpreting results, and effectively communicating your findings.

Essential Skills for a Statistician

Throughout the Track, you'll develop a strong foundation in key areas of statistics, including:

Probability theory and random variables
Regression analysis and predictive modeling
Sampling techniques and survey design
Hypothesis testing and inference
Experimental design and analysis
Bayesian data analysis
Factor analysis and latent variables

Solve Complex Problems with Real-World Data

Apply your statistical knowledge to tackle authentic challenges across business, engineering, and scientific domains. Learn to identify trends, make data-driven predictions, and provide actionable insights to stakeholders. By working with diverse datasets, you'll gain the practical experience needed to excel in a statistician role.

Leverage R for Statistical Analysis

R is the go-to programming language for statisticians due to its extensive collection of statistical packages and tools. In this Track, you'll learn to utilize R's capabilities to streamline your workflow and perform advanced analyses. From data manipulation with dplyr to creating visualizations with ggplot2, you'll master the essential tools of the trade.

Advance Your Career as a Statistician

Statisticians are in high demand across industries, with opportunities in finance, healthcare, technology, and more. By completing this Track, you'll have the skills and portfolio to:

Apply for statistician positions at top companies
Collaborate with cross-functional teams to drive data-informed decisions
Communicate statistical findings to both technical and non-technical audiences
Contribute to cutting-edge research and innovation
Advance your career with sought-after expertise

Whether you're an aspiring statistician or a professional looking to enhance your skills, this Track will equip you with the knowledge and practical experience to succeed in the field.

Persyaratan

Tidak ada persyaratan prasyarat untuk jalur ini.

Course
1
Introduction to Statistics in R
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.
Course
2
Foundations of Probability in R
In this course, you'll learn about the concepts of random variables, distributions, and conditioning.
Course
3
Introduction to Regression in R
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.
Course
4
Intermediate Regression in R
Learn to perform linear and logistic regression with multiple explanatory variables.
Course
7
Sampling in R
Master sampling to get more accurate statistics with less data.
Course
8
Hypothesis Testing in R
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.
Course
9
Experimental Design in R
In this course you'll learn about basic experimental design, a crucial part of any data analysis.
Course
13
Analyzing Survey Data in R
Learn survey design using common design structures followed by visualizing and analyzing survey results.
Course
15
Hierarchical and Mixed Effects Models in R
In this course you will learn to fit hierarchical models with random effects.
Course
16
Survival Analysis in R
Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!
Course
18
Fundamentals of Bayesian Data Analysis in R
Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.
Course
21
Factor Analysis in R
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.
Course
23
Foundations of Inference in R
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.
Project
bonus
How Environmental Factors Influence Wildlife Populations
Explore habitat data using factor and survival analysis tools.