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.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Data Analysis and Interpretation
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22,469 kürzliche Aufrufe
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Chi-Squared (Chi-2) DistributionData AnalysisStatistical Hypothesis TestingAnalysis Of Variance (ANOVA)
Lehrplan - Was Sie in diesem Kurs lernen werden
Woche
15 Stunden zum Abschließen
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 Videos (Gesamt 79 min), 11 Lektüren, 1 Quiz
14 Videos
Lesson 2 - From sample to population5m
Lesson 3 - Steps in hypothesis testing7m
Lesson 4 - What is a p value?5m
Lesson 5 - How to choose a statistical test1m
Lesson 6 - Ideas behind ANOVA9m
SAS Lesson 7 - ANOVA: Explanatory variable with 2 levels6m
SAS Lesson 8 - ANOVA: Explanatory variables with more than 2 levels2m
SAS Lesson 9 - Post hoc tests for ANOVA5m
SAS Lesson 10 - ANOVA summary2m
Python Lesson 7 - ANOVA: Explanatory variables with two levels8m
Python Lesson 8 - ANOVA: Explanatory variables with more than 2 levels3m
Python Lesson 9 - Post hoc tests for ANOVA5m
Python Lesson 10 - ANOVA Summary3m
11 Lektüren
Choosing SAS or Python10m
Getting Started with SAS10m
Getting Started with Python10m
Course Codebooks10m
Course Data Sets10m
Uploading Your Own Data to SAS10m
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
Getting set up for the assignments10m
Tumblr Instructions10m
Example: Running an analysis of variance10m
Woche
23 Stunden zum Abschließen
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 Videos (Gesamt 48 min), 3 Lektüren, 1 Quiz
7 Videos
SAS Lesson 2 - Chi Square Test of independence in practice5m
SAS Lesson 3 - Post hoc tests for Chi Square tests of independence10m
SAS Lesson 4 - Chi Square summary1m
Python Lesson 2 - Chi Square test of independence in practice8m
Python Lesson 3 - Post hoc tests for Chi Square tests of independence8m
Python Lesson 4 - Chi Square summary1m
3 Lektüren
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
Example: Running a Chi-Square Test of Independence10m
Woche
33 Stunden zum Abschließen
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 Videos (Gesamt 18 min), 2 Lektüren, 1 Quiz
4 Videos
Lesson 2 - Correlation Example3m
SAS Lesson 3 - Calculating Correlation4m
Python Lesson 3 - Calculating Correlation4m
2 Lektüren
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
Woche
43 Stunden zum Abschließen
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 Videos (Gesamt 51 min), 2 Lektüren, 1 Quiz
9 Videos
SAS Lesson 2 - Testing moderation in the context of ANOVA4m
SAS Lesson 3 - Testing moderation in the context of chi square6m
SAS Lesson 4 - Testing moderation in the context of correlation4m
Python Lesson 1 - Defining moderation, a.k.a. statistical interaction4m
Python Lesson 2 - Testing moderation in the context of ANOVA3m
Python Lesson 3 - Testing moderation in the context of Chi-Square4m
Python Lesson 4 - Testing moderation in the context of correlation4m
A Question of Causation (Used with Permission from Annenberg Learner)14m
2 Lektüren
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
29%
nahm einen neuen Beruf nach Abschluss dieser Kurse auf
33%
ziehen Sie für Ihren Beruf greifbaren Nutzen aus diesem Kurs
17%
erhalten Sie eine Gehaltserhöhung oder Beförderung
Top-Bewertungen von Data Analysis Tools
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.
Just love this whole specialisation! videos are great, lessons are great... it's just a great course! highly recommended to anyone looking to dive into the field of data analysis!
Dozenten
Jen Rose
Research ProfessorPsychology
Lisa Dierker
ProfessorPsychology
Über Wesleyan University
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.
Über den Spezialisierung Data Analysis and Interpretation
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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Sobald Sie sich für ein Zertifikat angemeldet haben, haben Sie Zugriff auf alle Videos, Quizspiele und Programmieraufgaben (falls zutreffend). Aufgaben, die von anderen Kursteilnehmern bewertet werden, können erst dann eingereicht und überprüft werden, wenn Ihr Unterricht begonnen hat. Wenn Sie sich den Kurs anschauen möchten, ohne ihn zu kaufen, können Sie womöglich auf bestimmte Aufgaben nicht zugreifen.
Was bekomme ich, wenn ich diese Spezialisierung abonniere?
Wenn Sie sich für den Kurs anmelden, erhalten Sie Zugriff auf alle Kurse der Spezialisierung und Sie erhalten nach Abschluss aller Arbeiten ein Zertifikat. Ihr elektronisches Zertifikat wird zu Ihrer Seite „Errungenschaften“ hinzugefügt – von dort können Sie Ihr Zertifikat ausdrucken oder es zu Ihrem LinkedIn Profil hinzufügen. Wenn Sie nur lesen und den Inhalt des Kurses anzeigen möchten, können Sie kostenlos als Gast an dem Kurs teilnehmen.
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