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Statistics for Data Scientists and Data Analysts

Histograms, Box Plot and Descriptive Statistics in R

Instructed by Phikolomzi Gugwana

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  • Student will immediately be able to apply data exploration methods to their day to day decision making

Learn how to make data-driven decisions in 35 minutes or less with this new and exciting course. In this course, you will be following along with the instructor instead of just watching. This course is also comprised entirely of examples so following along will be pretty easy. I was very excited to make this course. I'm very excited to share it with you and I hope to see you all inside.

  • R Studio
  • Data Scientists
  • Data Analysts
  • Business Analysts
  • Anyone who wants to brush up on their Statistics
  • Anyone who is curious about Data Science
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Section 1 : Unpublished Section

  • Lecture 1 :

Section 2 : Histograms

  • Lecture 1 :
  • Histogram
  • Lecture 2 :
  • Example 1: Student Marks
  • Lecture 3 :
  • Why do you want normality?
  • Lecture 4 :
  • Demo 1: Histogram of Marks
  • Lecture 5 :
  • Example 2: Freelancer Income
  • Lecture 6 :
  • Demo 2: Freelancer Income
  • Lecture 7 :
  • Quiz 1
  • Quiz 1

Section 3 : Box Plots

  • Lecture 1 :
  • Box Plots
  • Lecture 2 :
  • Example 3: Faulty Turbine
  • Lecture 3 :
  • How to tell if turbine is faulty
  • Lecture 4 :
  • Demo 3: Box plot of turbine output
  • Lecture 5 :
  • Example 4: Employee Performance
  • Lecture 6 :
  • Average and Consistency
  • Lecture 7 :
  • Demo 4: Employee Performance
  • Lecture 8 :
  • Quiz 2
  • Quiz 2

Section 4 : Descriptive Statistics

  • Lecture 1 :
  • Descriptive Statistics
  • Lecture 2 :
  • What are descriptive statistics?
  • Lecture 3 :
  • Definitions of descriptive statistics
  • Lecture 4 :
  • Example 5
  • Lecture 5 :
  • Example 5 Breakdown
  • Lecture 6 :
  • Demo: Example 5
  • Lecture 7 :
  • Example 6
  • Lecture 8 :
  • Example 6 Breakdown
  • Lecture 9 :
  • Demo: Example 6
  • Lecture 10 :
  • Example 7
  • Lecture 11 :
  • Example 7 Breakdown
  • Lecture 12 :
  • Example 7 Demo
  • Lecture 13 :
  • Course Conclusion
  • Lecture 14 :
  • Quiz 3
  • Quiz 3

Section 5 : Hypothesis Testing

  • Lecture 1 :
  • Hypothesis Testing

Phikolomzi Gugwana,

I am a Data Scientist with a background in Statistics and Economics. I have experience in the oil and gas industry. I have a passion for learning and teaching. I believe that the solutions to the world's problems will come if we share knowledge and work together.
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