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Inferential Statistical Analysis with Python
  • Level Professional
  • المدة 19 ساعات hours
  • الطبع بواسطة University of Michigan
  • Offered by

عن

In this course, we will explore basic principles behind using data for estimation and for assessing theories. We will analyze both categorical data and quantitative data, starting with one population techniques and expanding to handle comparisons of two populations. We will learn how to construct confidence intervals. We will also use sample data to assess whether or not a theory about the value of a parameter is consistent with the data. A major focus will be on interpreting inferential results appropriately. At the end of each week, learners will apply what they've learned using Python within the course environment. During these lab-based sessions, learners will work through tutorials focusing on specific case studies to help solidify the week's statistical concepts, which will include further deep dives into Python libraries including Statsmodels, Pandas, and Seaborn. This course utilizes the Jupyter Notebook environment within Coursera.

الوحدات

Introduction to this Course

    • 2 Videos
    • 5 Readings
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2 Videos

  • Welcome to the Course!
  • Inferential Statistical Analysis with Python Guidelines

5 Readings

  • Course Syllabus
  • Meet the Course Team!
  • Formula Help Sheets
  • About Our Datasets
  • Help Us Learn More About You!

Inference Procedures

    • 3 Videos
    • 1 Readings
    • 1 Discussion
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1 Discussions

  • Research Questions in Real Life

3 Videos

  • Introduction to Inference Methods: Oh the Things You Will See!
  • Bag A or Bag B?
  • This or That? Language and Notation

1 Readings

  • This or That Reference

Using Python in this course

    • 1 Videos
    • 1 Readings
    • 2 Lab
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2 Labs

  • Review of Course 1 Python Concepts
  • Functions and Lambda Functions, Reading Help Files

1 Videos

  • The Python Statistics Landscape

1 Readings

  • Python Statistical Functions Cheat Sheet

Python Assessment

    • 1 Lab
    • 1 Assignment
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1 Assignment

  • Python Basics Assessment

1 Labs

  • Python Basics Assessment Notebook

One Proportion

    • 5 Videos
    • 2 Assignment
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2 Assignment

  • Practice Quiz: All About Confidence Intervals
  • Sample Size & Assumptions

5 Videos

  • Estimating a Population Proportion with Confidence
  • Understanding Confidence Intervals
  • Demo: Seeing Theory
  • Assumptions for a Single Population Proportion Confidence Interval
  • Conservative Approach & Sample Size Consideration

Two Proportions

    • 2 Videos
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2 Videos

  • Estimating a Difference in Population Proportions with Confidence
  • Interpretations & Assumptions for Two Population Proportion Intervals

One Mean

    • 1 Videos
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1 Videos

  • Estimating a Population Mean with Confidence

Difference in Means for Paired Data

    • 1 Videos
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1 Videos

  • Estimating a Mean Difference for Paired Data

Difference in Means for Independent Groups

    • 1 Videos
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1 Videos

  • Estimating a Difference in Population Means with Confidence (for Independent Groups)

Other Inference Considerations

    • 3 Readings
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3 Readings

  • Confidence Intervals: Other Considerations
  • What Affects the Standard Error of an Estimate?
  • t-distributions vs. z-distributions

Confidence Intervals in Python

    • 1 Readings
    • 5 Lab
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5 Labs

  • Introduction to Confidence Intervals in Python
  • Confidence Intervals for Differences between Population Parameters
  • Case Study Using Confidence Intervals with NHANES
  • More Practice: Confidence intervals with NHANES
  • Solutions to "More Practice: Confidence intervals with NHANES"

1 Readings

  • Additional Practice: An Introductory Guide to PDFs and CDFs

Python Assessment

    • 1 Readings
    • 1 Lab
    • 1 Assignment
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1 Assignment

  • Confidence Intervals Assessment

1 Labs

  • Confidence Intervals in Python Assessment Notebook

1 Readings

  • Napping and Non-Napping Toddlers Article for Python Assessment

One Proportion

    • 2 Videos
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2 Videos

  • Setting Up a Test for a Population Proportion
  • Testing a One Population Proportion

Two Proportions

    • 2 Videos
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2 Videos

  • Setting Up a Test of Difference in Population Proportions
  • Testing a Difference in Population Proportions

P-Values

    • 1 Videos
    • 1 Discussion
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1 Discussions

  • P-Values and P-Hacking

1 Videos

  • Interview: P-Values, P-Hacking and More

One Mean

    • 1 Videos
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1 Videos

  • One Mean: Testing about a Population Mean with Confidence

Difference in Means for Paired Data

    • 1 Videos
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1 Videos

  • Testing a Population Mean Difference

Difference in Means for Independent Groups

    • 1 Videos
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1 Videos

  • Testing for a Difference in Population Means (for Independent Groups)

More Inference Considerations

    • 1 Videos
    • 2 Readings
    • 1 Assignment
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1 Assignment

  • Name That Scenario

1 Videos

  • Demo: Name That Scenario

2 Readings

  • Hypothesis Testing: Other Considerations
  • The Relationship between Confidence Intervals & Hypothesis Testing

Writing Assignment

    • 1 Videos
    • 1 PeerReview
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1 Peer Review

  • Chocolate & Cycling Assignment

1 Videos

  • Chocolate & Cycling Assignment

Hypothesis Testing in Python

    • 5 Lab
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5 Labs

  • Introduction to Hypothesis Testing in Python
  • Walk-Through: Hypothesis Testing with NHANES
  • Case Study Using Hypothesis Testing with NHANES
  • More Practice: Hypothesis testing with NHANES
  • Solutions to "More Practice: Hypothesis testing with NHANES"

Python Assessment

    • 1 Lab
    • 1 Assignment
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1 Assignment

  • Hypothesis Testing in Python Assessment

1 Labs

  • Hypothesis Testing in Python Assessment Notebook

Learner Application

    • 6 Videos
    • 3 Readings
    • 1 Assignment
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1 Assignment

  • Assessment

6 Videos

  • The Importance of Good Research Questions for Sound Inference
  • Descriptive Inference Examples for Single Variables Using Confidence Intervals
  • Descriptive Inference Examples for Single Variables Using Hypothesis Testing
  • Comparing Means for Two Independent Samples: An Example
  • Comparing Means for Two Paired Samples: An Example
  • Comparing Proportions for Two Independent Samples: An Example

3 Readings

  • Assumptions Consistency
  • Comparing Proportions for Two Independent Samples
  • Revisiting Examples: Accounting for Complex Samples

Course Feedback

    • 2 Readings
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2 Readings

  • Course Feedback
  • Keep Learning with Michigan Online

Auto Summary

Discover key principles of data estimation and theory assessment in "Inferential Statistical Analysis with Python." This professional-level course, led by Coursera, focuses on both categorical and quantitative data, teaching you to construct confidence intervals and test theories using Python. Engage in lab-based sessions each week, utilizing Python libraries like Statsmodels, Pandas, and Seaborn in Jupyter Notebook. With a total duration of 1140 minutes, flexible subscription options include Starter, Professional, and Paid plans, making it ideal for aspiring data scientists and AI professionals.

Brenda Gunderson
Instructors

Brenda Gunderson

Brady T. West
Instructors

Brady T. West

Kerby Shedden
Instructors

Kerby Shedden