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Statistical Thinking in Python (Part 2)

Intermediate
4.6+
17 reviews
Updated 12/2024
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.
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PythonProbability & Statistics4 hours15 videos66 exercises5,350 XP91,135Statement of Accomplishment

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Course Description

After completing Statistical Thinking in Python (Part 1), you have the probabilistic mindset and foundational hacker stats skills to dive into data sets and extract useful information from them. In this course, you will do just that, expanding and honing your hacker stats toolbox to perform the two key tasks in statistical inference, parameter estimation and hypothesis testing. You will work with real data sets as you learn, culminating with analysis of measurements of the beaks of the Darwin's famous finches. You will emerge from this course with new knowledge and lots of practice under your belt, ready to attack your own inference problems out in the world.

Prerequisites

Statistical Thinking in Python (Part 1)
1

Parameter estimation by optimization

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2

Bootstrap confidence intervals

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3

Introduction to hypothesis testing

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4

Hypothesis test examples

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5

Putting it all together: a case study

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Statistical Thinking in Python (Part 2)
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*4.6
from 17 reviews
76%
18%
0%
6%
0%
  • Ildar K.
    12 days

    Thanks for this course

  • Kleopatra R.
    3 months

    I think that the Datacamp site can benefit from more courses on statistical analysis. This is the connection between python programming and our data analysis. I can always google my way through scripts, but understanding what it is that I am looking for is necessary.

  • Thomas M.
    11 months

    The two Statistical Thinking courses provide an excellent introduction to statistical analysis with Python. The theoretical background is well explained and the hands-on excercises are designed to learn step-by-step how to apply the statistical tools in Python. In my opinion, these 2 courses are among the very best DataCamp has to offer. The lecturer succeeds in translating his fascination with his professional approach to statistics

  • Tim K.
    about 1 year

    Good course that teaches statistics and methods

  • Laura L.
    about 1 year

    Great

"Thanks for this course"

Ildar K.

"I think that the Datacamp site can benefit from more courses on statistical analysis. This is the connection between python programming and our data analysis. I can always google my way through scripts, but understanding what it is that I am looking for is necessary."

Kleopatra R.

"Good course that teaches statistics and methods"

Tim K.

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