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Statistician in R

A statistician collects and analyzes data and helps companies make sense of quantitative data, including spotting trends and making predictions.
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RProbability & Statistics52 hours11,960

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Track Description

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.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Introduction to Statistics in R

    Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

  • 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

    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

    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

    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.

Statistician in R
13 Courses
Track
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