Udemy

Statistics for Data Analysis Using R

立即報名
  • 13,734 名學生
  • 更新於 9/2021
4.7
(2,589 個評分)
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課程資料

報名日期*
全年招生
課程級別
學習模式
修業期
12 小時 25 分鐘
教學語言
英語
授課導師
Sandeep Kumar, ­ Quality Gurus Inc.
評分
4.7
(2,589 個評分)
*提示: 以上時間表僅供參考,以機構網站為準。

課程簡介

Statistics for Data Analysis Using R

Learn Programming in R & R Studio • Descriptive, Inferential Statistics • Plots for Data Visualization • Data Science

Perform simple or complex statistical calculations using R Programming! - You don't need to be a programmer for this :)

Learn statistics, and apply these concepts in your workplace using R.

The course will teach you the basic concepts related to Statistics and Data Analysis,  and help you in applying these concepts. Various examples and data sets are used to explain the application.

I will explain the basic theory first, and then I will show you how to use R to perform these calculations.

The following areas of statistics are covered:

Descriptive Statistics - Mean, Mode, Median, Quartile, Range, Inter Quartile Range, Standard Deviation. (Using base R function and the psych package)

Data Visualization - 3 commonly used charts: Histogram, Box and Whisker Plot and Scatter Plot (using base R commands)

Probability - Basic Concepts, Permutations, Combinations (Basic theory only)

Population and Sampling - Basic concepts (theory only)

Probability Distributions - Normal, Binomial  and Poisson Distributions (Base R functions and the visualize package)

Hypothesis Testing - One Sample and Two Samples - z Test, t-Test, F Test, Chi-Square Test

ANOVA - Perform Analysis of Variance (ANOVA) step by step doing the manual calculation and by using R.


What are other students saying about this course?

  • This course is a perfect mix of theory and practice. I highly recommend it for those who want to not only get good with R, but to also become proficient in statistics. (5 stars by Aaron Verive)

  • You get both the “how” and “why” for both the statistics and R programming. I’m really happy with this course. (5 stars by Elizabeth Crook)

  • Sandeep has such a clear approach, pedagogic and explains everything he does. Perfect for a novice like myself. (5 stars by Hashim Al-Haboobi)

  • Very clear explanation. Coming from a non-technical background, it is immensely helpful that Prof. Sandeep Kumar is explaining all the minor details to prevent any scope for confusion. (5 stars by Ann Mary Biju)

  • I had a limited background in R and statistics going into this course. I feel like this gave me the perfect foundation to progress to more complex topics in both of those areas. I'm very happy I took this course. (5 stars by Thach Phan)

  • Dr. Kumar is a fantastic teacher who takes you step by step. Can't say enough about his approach. Detailed. Not only clear descriptions of statistics but you will learn many details that make R easier to use and understand. (5 stars by James Reynolds)

  • This is a wonderful course, I do recommend it. The best Udemy course I took. (5 stars by Joao Alberto Arantes Do Amaral)

  • The course exceeded my expectations and i would like to thank the instructor Mr Sandeep Kumar for creating such an amazing course. The best thing about this course is the Theory incorporated that helps you understand what you are going to code in R. I have really learnt a lot. If you a looking for the best course for R then look no further because this is the best there can be. (5 stars by Kipchumba Brian)


What are you waiting for?

This course comes with Udemy's 30 days money-back guarantee. If you are not satisfied with the course, get your money back.

I hope to see you in the course.

課程章節

  • 10 個章節
  • 111 堂課
  • 第 1 章 1. Getting Started with R and R Studio
  • 第 2 章 2. Bonus Section: Descriptive Statistics Theory (lessons from my other course)
  • 第 3 章 3. Descriptive Statistics Using R
  • 第 4 章 4. Vectors, Factors, Lists, Matrix and Data Frames in R
  • 第 5 章 5. Data Visualization
  • 第 6 章 6. Descriptive Statistics Re-visited
  • 第 7 章 7. Bonus Section: Basic Probability Theory (lessons from my other course)
  • 第 8 章 8. Probability Distributions
  • 第 9 章 9. Inferential Statistics - Hypothesis Tests
  • 第 10 章 Bonus Section

課程內容

  • Learn R programming from the ground up, starting from the basics and progressing to advanced data analysis techniques.
  • Learn the basic statistical concepts first, followed by practical application using R Studio, combining theory and practice for effective learning.
  • Master descriptive statistics, including mean, mode, median, skewness, and kurtosis, and how to apply these concepts to your data analysis.
  • Understand and perform inferential statistics such as one and two-sample z-tests, t-tests, Chi-Square tests, F-tests, ANOVA, and TukeyHSD, and more.
  • Explore probability distributions, including normal, binomial, and Poisson, and their applications in data analysis.
  • Develop the skills to perform data manipulation, visualization, and statistical analysis using R.
  • Apply statistical concepts in real-world scenarios, enhancing your problem-solving abilities and decision-making skills.
  • Boost your career prospects with a strong foundation in statistics and R programming, valuable skills in today’s data-driven job market.
  • Equip yourself with the tools to handle large datasets and perform complex statistical analyses with confidence.
  • Enhance your ability to make data-driven decisions by mastering the use of R for statistical analysis.

評價

  • R
    Raymond Daly
    5.0

    Well explained.. & easy to follow worked-out examples

  • C
    Caden Jon Howard
    4.5

    Yes, its helping me improve my skills in R.

  • P
    Paritosh Kadam
    5.0

    Training was good

  • M
    Munyawiri Blessing
    5.0

    As a student for a master's in public health, I am enjoying every bit of this course. The teachers do well on practical aspects, and you can easily follow. He further enriches with theoretical statistical knowledge, which is a cornerstone in understanding statistics. I don't regret parting with my dollars.Hopeful to be a guru in R

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