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.
Ce cours fait partie de la Spécialisation Statistics with Python
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À propos de ce cours
High school algebra, successful completion of Course 1 in this specialization or equivalent background
Ce que vous allez apprendre
Determine assumptions needed to calculate confidence intervals for their respective population parameters.
Create confidence intervals in Python and interpret the results.
Review how inferential procedures are applied and interpreted step by step when analyzing real data.
Run hypothesis tests in Python and interpret the results.
Compétences que vous acquerrez
- Confidence Interval
- Python Programming
- Statistical Inference
- Statistical Hypothesis Testing
High school algebra, successful completion of Course 1 in this specialization or equivalent background
Offert par
Programme de cours : ce que vous apprendrez dans ce cours
WEEK 1 - OVERVIEW & INFERENCE PROCEDURES
WEEK 2 - CONFIDENCE INTERVALS
WEEK 3 - HYPOTHESIS TESTING
WEEK 4 - LEARNER APPLICATION
Avis
- 5 stars74,13 %
- 4 stars17,36 %
- 3 stars5,50 %
- 2 stars1,55 %
- 1 star1,43 %
Meilleurs avis pour INFERENTIAL STATISTICAL ANALYSIS WITH PYTHON
Thank you a lot. For me was an incredible course I learned many things and was very important to my career. Thanks to all the team, They are really masters.
It was very good course, everything was very well explained and the activities were challenging enough to practice the knowledges obtain.
Great course with practical experience with Python. There are many courses that teach statistics with R but this is the first one to do so in Python.
Good theoretical foundation, but lacks explanation on python libraries extensively used in the course.
À propos du Spécialisation Statistics with Python

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