In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question. Using your choice of two powerful statistical software packages (SAS or Python), you will explore ANOVA, Chi-Square, and Pearson correlation analysis. This course will guide you through basic statistical principles to give you the tools to answer questions you have developed. Throughout the course, you will share your progress with others to gain valuable feedback and provide insight to other learners about their work.
Ce cours fait partie de la Spécialisation Analyse et interprétation de données
Outils d'analyse des données
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À propos de ce cours
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Compétences que vous acquerrez
Chi-Squared (Chi-2) DistributionData AnalysisStatistical Hypothesis TestingAnalysis Of Variance (ANOVA)
Programme du cours : ce que vous apprendrez dans ce cours
Semaine
15 heures pour terminer
Hypothesis Testing and ANOVA
This session starts where the Data Management and Visualization course left off. Now that you have selected a data set and research question, managed your variables of interest and visualized their relationship graphically, we are ready to test those relationships statistically. The first group of videos describe the process of hypothesis testing which you will use throughout this course to test relationships between different kinds of variables (quantitative and categorical). Next, we show you how to test hypotheses in the context of Analysis of Variance (when you have one quantitative variable and one categorical variable). Your task will be to write a program that manages any additional variables you may need and runs and interprets an Analysis of Variance test. Note that if your research question does not include one quantitative variable, you can use one from your data set just to get some practice with the tool. If your research question does not include a categorical variable, you can categorize one that is quantitative.
14 vidéos (Total 79 min), 11 lectures, 1 quiz
14 vidéos
Lesson 2 - From sample to population5 min
Lesson 3 - Steps in hypothesis testing7 min
Lesson 4 - What is a p value?5 min
Lesson 5 - How to choose a statistical test1 min
Lesson 6 - Ideas behind ANOVA9 min
SAS Lesson 7 - ANOVA: Explanatory variable with 2 levels6 min
SAS Lesson 8 - ANOVA: Explanatory variables with more than 2 levels2 min
SAS Lesson 9 - Post hoc tests for ANOVA5 min
SAS Lesson 10 - ANOVA summary2 min
Python Lesson 7 - ANOVA: Explanatory variables with two levels8 min
Python Lesson 8 - ANOVA: Explanatory variables with more than 2 levels3 min
Python Lesson 9 - Post hoc tests for ANOVA5 min
Python Lesson 10 - ANOVA Summary3 min
11 lectures
Choosing SAS or Python10 min
Getting Started with SAS10 min
Getting Started with Python10 min
Course Codebooks10 min
Course Data Sets10 min
Uploading Your Own Data to SAS10 min
SAS Program Code for Video Examples10 min
Python Program Code for Video Examples10 min
Getting set up for the assignments10 min
Tumblr Instructions10 min
Example: Running an analysis of variance10 min
Semaine
23 heures pour terminer
Chi Square Test of Independence
This session shows you how to test hypotheses in the context of a Chi-Square Test of Independence (when you have two categorical variables). Your task will be to write a program that manages any additional variables you may need and runs and interprets a Chi-Square Test of Independence. Note that if your research question only includes quantitative variables, you can categorize those just to get some practice with the tool.
7 vidéos (Total 48 min), 3 lectures, 1 quiz
7 vidéos
SAS Lesson 2 - Chi Square Test of independence in practice5 min
SAS Lesson 3 - Post hoc tests for Chi Square tests of independence10 min
SAS Lesson 4 - Chi Square summary1 min
Python Lesson 2 - Chi Square test of independence in practice8 min
Python Lesson 3 - Post hoc tests for Chi Square tests of independence8 min
Python Lesson 4 - Chi Square summary1 min
3 lectures
SAS Program Code for Video Examples10 min
Python Program Code for Video Examples10 min
Example: Running a Chi-Square Test of Independence10 min
Semaine
33 heures pour terminer
Pearson Correlation
This session shows you how to test hypotheses in the context of a Pearson Correlation (when you have two quantitative variables). Your task will be to write a program that manages any additional variables you may need and runs and interprets a correlation coefficient. Note that if your research question only includes categorical variables, you can choose other variables from your data set just to get some practice with the tool.
4 vidéos (Total 18 min), 2 lectures, 1 quiz
4 vidéos
Lesson 2 - Correlation Example3 min
SAS Lesson 3 - Calculating Correlation4 min
Python Lesson 3 - Calculating Correlation4 min
2 lectures
SAS Program Code for Video Examples10 min
Python Program Code for Video Examples10 min
Semaine
43 heures pour terminer
Exploring Statistical Interactions
In this session, we will discuss the basic concept of statistical interaction (also known as moderation). In statistics, moderation occurs when the relationship between two variables depends on a third variable. The effect of a moderating variable is often characterized statistically as an interaction; that is, a third variable that affects the direction and/or strength of the relation between your explanatory (X) and response (Y) variable. Your task will be to test your own research question in the context of one or more potential moderating variables.
9 vidéos (Total 51 min), 2 lectures, 1 quiz
9 vidéos
SAS Lesson 2 - Testing moderation in the context of ANOVA4 min
SAS Lesson 3 - Testing moderation in the context of chi square6 min
SAS Lesson 4 - Testing moderation in the context of correlation4 min
Python Lesson 1 - Defining moderation, a.k.a. statistical interaction4 min
Python Lesson 2 - Testing moderation in the context of ANOVA3 min
Python Lesson 3 - Testing moderation in the context of Chi-Square4 min
Python Lesson 4 - Testing moderation in the context of correlation4 min
A Question of Causation (Used with Permission from Annenberg Learner)14 min
2 lectures
SAS Program Code for Video Examples10 min
Python Program Code for Video Examples10 min
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Voir les conditions4.5
77 avis29%
ont commencé une nouvelle carrière après avoir terminé ce cours
33%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
17%
a obtenu une augmentation de salaire ou une promotion
Meilleurs avis pour Outils d'analyse des données
Again, with no formal SAS training and minimal statistics background. I found taking the first course and then this course - week after week my knowledge grew in a consistent and organized fashion.
Very good for beginners. concept explanation as well as coding were great. doesn't take too long to finish. I enrolled regression modeling course by Wesleyan and waiting to start.
Enseignants
Jen Rose
Research ProfessorPsychology
Lisa Dierker
ProfessorPsychology
À propos de Université Wesleyenne
At Wesleyan, distinguished scholar-teachers work closely with students, taking advantage of fluidity among disciplines to explore the world with a variety of tools. The university seeks to build a diverse, energetic community of students, faculty, and staff who think critically and creatively and who value independence of mind and generosity of spirit.
À propos du Spécialisation Analyse et interprétation de données
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions.
The Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights. In the Capstone Project, you will use real data to address an important issue in society, and report your findings in a professional-quality report. You will have the opportunity to work with our industry partners, DRIVENDATA and The Connection. Help DRIVENDATA solve some of the world's biggest social challenges by joining one of their competitions, or help The Connection better understand recidivism risk for people on parole in substance use treatment. Regular feedback from peers will provide you a chance to reshape your question. This Specialization is designed to help you whether you are considering a career in data, work in a context where supervisors are looking to you for data insights, or you just have some burning questions you want to explore. No prior experience is required. By the end you will have mastered statistical methods to conduct original research to inform complex decisions.
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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.
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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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