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
Inferential Statistical Analysis with Python
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À propos de ce cours
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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 IntervalPython ProgrammingStatistical InferenceStatistical Hypothesis Testing
Résultats de carrière des étudiants
50%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
50%
a obtenu une augmentation de salaire ou une promotion
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 2 sur 3 dans le
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
High school algebra, successful completion of Course 1 in this specialization or equivalent background
Approx. 10 heures pour terminer
Recommandé : 4 weeks of study, 4-6 hours/week
Anglais
Sous-titres : Anglais, Coréen
Programme du cours : ce que vous apprendrez dans ce cours
3 heures pour terminer
WEEK 1 - OVERVIEW & INFERENCE PROCEDURES
In this first week, we’ll review the course syllabus and discover the various concepts and objectives to be mastered in weeks to come. You’ll be introduced to inference methods and some of the research questions we’ll discuss in the course, as well as an overall framework for making decisions using data, considerations for how you make those decisions, and evaluating errors that you may have made.
3 heures pour terminer
9 vidéos (Total 67 min), 5 lectures, 1 quiz
9 vidéos
Inferential Statistical Analysis with Python Guidelines4 min
Introduction to Inference Methods: Oh the Things You Will See!3 min
Bag A or Bag B?13 min
Introduction to Bayesian4 min
This or That? Language and Notation13 min
The Python Statistics Landscape2 min
Intermediate Python Concepts: Lists vs Numpy Arrays10 min
Functions and Lambda Functions, Reading Help Files11 min
5 lectures
Course Syllabus5 min
Meet the Course Team!10 min
About Our Datasets2 min
Help Us Learn More About You!10 min
This or That Reference10 min
1 exercice pour s'entraîner
Python Basics Assessment15 min
5 heures pour terminer
WEEK 2 - CONFIDENCE INTERVALS
In this second week, we will learn about estimating population parameters via confidence intervals. You will be introduced to five different types of population parameters, assumptions needed to calculate a confidence interval for each of these five parameters, and how to calculate confidence intervals. Quizzes will appear throughout the week to test your understanding. In addition, you’ll learn how to create confidence intervals in Python.
5 heures pour terminer
12 vidéos (Total 118 min), 3 lectures, 3 quiz
12 vidéos
Understanding Confidence Intervals10 min
Demo: Seeing Theory5 min
Assumptions for a Single Population Proportion Confidence Interval3 min
Conservative Approach & Sample Size Consideration8 min
Estimating a Difference in Population Proportions with Confidence6 min
Interpretations & Assumptions for Two Population Proportion Intervals4 min
Estimating a Population Mean with Confidence14 min
Estimating a Mean Difference for Paired Data10 min
Estimating a Difference in Population Means with Confidence (for Independent Groups)14 min
Introduction to Confidence Intervals in Python12 min
Confidence Intervals for Differences between Population Parameters21 min
3 lectures
Confidence Intervals: Other Considerations15 min
What Affects the Standard Error of an Estimate?10 min
Additional Practice: Confidence Intervals1 min
3 exercices pour s'entraîner
Practice Quiz: All About Confidence Intervals30 min
Sample Size & Assumptions
Confidence Intervals Assessment1 h
6 heures pour terminer
WEEK 3 - HYPOTHESIS TESTING
In week three, we’ll learn how to test various hypotheses - using the five different analysis methods covered in the previous week. We’ll discuss the importance of various factors and assumptions with hypothesis testing and learn to interpret our results. We will also review how to distinguish which procedure is appropriate for the research question at hand. Quizzes and a peer assessment will appear throughout the week to test your understanding.
6 heures pour terminer
12 vidéos (Total 138 min), 4 lectures, 3 quiz
12 vidéos
Testing a One Population Proportion8 min
Setting Up a Test of Difference in Population Proportions7 min
Testing a Difference in Population Proportions8 min
Interview: P-Values, P-Hacking and More24 min
One Mean: Testing about a Population Mean with Confidence17 min
Testing a Population Mean Difference13 min
Testing for a Difference in Population Means (for Independent Groups)12 min
Demo: Name That Scenario2 min
Chocolate & Cycling Assignment2 min
Introduction to Hypothesis Testing in Python20 min
Walk-Through: Hypothesis Testing with NHANES13 min
4 lectures
Hypothesis Testing: Other Considerations10 min
The Relationship between Confidence Intervals & Hypothesis Testing5 min
Chocolate & Cycling Assignment Instructions5 min
Additional Practice: Hypothesis Testing1 min
2 exercices pour s'entraîner
Name That Scenario15 min
Hypothesis Testing in Python Assessment1 h
4 heures pour terminer
WEEK 4 - LEARNER APPLICATION
In the final week of this course, we will walk through several examples and case studies that illustrate applications of the inferential procedures discussed in prior weeks. Learners will see examples of well-formulated research questions related to the study designs and data sets that we have discussed thus far, and via both confidence interval estimation and formal hypothesis testing, we will formulate inferential responses to those questions.
4 heures pour terminer
6 vidéos (Total 77 min), 3 lectures, 1 quiz
6 vidéos
Descriptive Inference Examples for Single Variables Using Confidence Intervals12 min
Descriptive Inference Examples for Single Variables Using Hypothesis Testing12 min
Comparing Means for Two Independent Samples: An Example14 min
Comparing Means for Two Paired Samples: An Example12 min
Comparing Proportions for Two Independent Samples: An Example13 min
3 lectures
Assumptions Consistency5 min
Revisiting Examples: Accounting for Complex Samples10 min
Course Feedback10 min
1 exercice pour s'entraîner
Assessment30 min
Avis
4.5
Meilleurs avis pour INFERENTIAL STATISTICAL ANALYSIS WITH PYTHON
par SSMar 19, 2020
Great Course. There are so many example to understand the topic. I really enjoyed every lesson of this specialization. I am going forward for the next one.
par RRMar 6, 2019
If you are interested in statistics and statistical analysis, this course gets you grounded in the essential aspects of statistics. Excellent instructors.
par JXJun 21, 2019
A very in-depth learning material for inferential statistics. Very good explanation of p-value which clarifies some of the prevailing misunderstandings.
par YBMay 28, 2019
This course is significantly better than the previous one. Nevertheless, if you want to get knowledge about Python, it’s not about this course.
par MGSep 10, 2019
It was very good course, everything was very well explained and the activities were challenging enough to practice the knowledges obtain.
par JNOct 13, 2019
Good Python tutorials that gives a good paratactical introduction to the theoretical core of the course.
par YPJul 7, 2019
Good theoretical foundation, but lacks explanation on python libraries extensively used in the course.
par QQFeb 23, 2020
This is the first certificate I got in Coursera. I like this course, especially then notebook part
par SFJan 26, 2020
Overall solid course. Could do without peer review assignment, more of a hassle than anything.
par KAMar 22, 2020
Perfect Course, It was very useful to understand the basics of inferential statistics
par PKJul 16, 2019
The content explanation is excellent and one of the best I have seen.
par FFMar 22, 2020
It's an amazing course! very clear, very informative!!
par BGFeb 23, 2020
Need Intermediate - Advanced skill level in Python.
Offert par
Université du Michigan
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
À propos du Spécialisation Statistics with Python
This specialization is designed to teach learners beginning and intermediate concepts of statistical analysis using the Python programming language. Learners will learn where data come from, what types of data can be collected, study data design, data management, and how to effectively carry out data exploration and visualization. They will be able to utilize data for estimation and assessing theories, construct confidence intervals, interpret inferential results, and apply more advanced statistical modeling procedures. Finally, they will learn the importance of and be able to connect research questions to the statistical and data analysis methods taught to them.
Foire Aux Questions
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Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.
À quoi ai-je droit si je m'abonne à cette Spécialisation ?
Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.
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