Statistics for Data Science 2018 Part 1 | Statistics Tutorial For Beginners | Data Science Tutorial {VIDEO}

Statistics for Data Science 2018 Part 1 | Statistics Tutorial for Beginners | Data Science Tutorial
Hello and Welcome to one of the Best Data Science tutorial conducted by Acadgild. This video talks about applications of statistics for data science. Let’s check the topics covered in this tutorial.
After completing this training session, you will be able to learn,
• Introduction to Statistics
• Basic Statistics
• Introduction to the Basic Terms of Statistics
• What are Variables
• The Measure of Central Tendency the Mean, Median, and Mode
• The Measures of Dispersion
• What is a Range
• What is Sample Variance
• Standard Deviation
• Population Vs Sample
• What is Chebysheff’s Theorem
• Law of Expected Values and Variance
• Probability Density Function
Check out the basic terms used in statistics: Variable, Data (singular), Data (plural), Experiment, Parameter, Statistics.
Kinds of Variables or Types of Variable: Qualitative or Attributive or Categorical variable

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  1. THE best in class lecture in the topic..I'd be more happy, if you kept your work window (PC etc) into inset PIP…cause we need to go back and forth to see formulae.

  2. Hi Gentleman, you are a great communicator, your lecture delivery is simply superb, your way of teaching has attracted my attention.

  3. Hi Sir, This is awesome site for newbies in Data Science to understand the concept of Statistics. I liked it the way you explained the concepts, though its simple but effective.

  4. Sir, please check the example of two section of classes. In section B when you are calculating the average you are dividing by 50. I think it should be 100. Please confirm. Thanks in advance.

  5. Very Informative but the examples used are too boring and old. Can't we use new examples which are actually related to current situations or data science? These are old school examples from which attention gets diverted and the video gets boring, other YouTubers are using examples from their work(data science) or current situations. please do it differently not old school teachers. thanks

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