Statistical Data Analysis with Python Online Tutorials in 2022

Statistical Data Analysis: Carry out Statistical Information Evaluation Methods with the Python Programming Language. Apply Pocketbook included.

Statistical Data Analysis with Python Online Tutorials


By the tip of this course, you’ll have achieved the next studying outcomes:

  • Clarify and calculate the significance of measures of central tendency.
  • Clarify and calculate the significance of measures of dispersion.
  • Establish the relative strengths and weaknesses of the measures of tendency.
  • Establish the relative strengths and weaknesses of the measures of dispersion.
  • Create and interpret a histogram, a bar chart, a field plot, and a frequency desk.
  • Establish and describe scatter plots and line graphs to find out the relationships between two variables.
  • Calculate and interpret the Pearson correlation coefficient to find out the relationships between two variables. 

These are a number of the foundation of statistical knowledge evaluation methods that you’ll get to make use of whereas engaged on knowledge science tasks. For instance, with the intention to test for mannequin assumptions whereas engaged on a predictive resolution, you’ll need to use the above methods i.e. to check for normality of variables in a dataset, you may plot a histogram or a pair plot, to test for correlation, you may calculate the Pearson correlation coefficient, and many others.

As well as, these methods can even be essential whereas additionally engaged on knowledge evaluation tasks the place the creation of a descriptive evaluation report will probably be a necessity.

What you’ll learn

  • Clarify and calculate the significance of measures of central tendency.
  • Clarify and calculate the significance of measures of dispersion.
  • Establish the relative strengths and weaknesses of the measures of tendency.
  • Establish the relative strengths and weaknesses of the measures of dispersion.
  • Create and interpret a histogram, a bar chart, a field plot, and a frequency desk.
  • Establish and describe scatter plots and line graphs to find out the relationships between two variables.
  • Calculate and interpret the Pearson correlation coefficient to find out the relationships between two variables.

Are there any course requirements or conditions?

  • To have fundamental python programming proficiency.
  • You’ll need a contemporary browser i.e. Google Chrome or Mozilla Firefox.

Who this course is for:

  • This course is designed for professionals with a curiosity in getting hands-on expertise with the respective knowledge science methods and instruments.

Disclaimer: If the link given in this post is from a free tutorial. Which is taken from the website of udemy.com. If it violates any policy. So please contact. After that, we will remove the link

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