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.
Este curso faz parte do Programa de cursos integrados Análise e interpretação de dadosAnálise e Interpretação de Dados
oferecido por
Informações sobre o curso
Habilidades que você terá
- Chi-Squared (Chi-2) Distribution
- Data Analysis
- Statistical Hypothesis Testing
- Analysis Of Variance (ANOVA)
oferecido por

Universidade Wesleyan
Wesleyan University, founded in 1831, is a diverse, energetic liberal arts community where critical thinking and practical idealism go hand in hand. With our distinctive scholar-teacher culture, creative programming, and commitment to interdisciplinary learning, Wesleyan challenges students to explore new ideas and change the world. Our graduates go on to lead and innovate in a wide variety of industries, including government, business, entertainment, and science.
Programa - O que você aprenderá com este curso
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.
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.
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.
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.
Avaliações
- 5 stars68,81%
- 4 stars21,78%
- 3 stars5,69%
- 2 stars2,22%
- 1 star1,48%
Principais avaliações do FERRAMENTAS ESTATÍSTICAS PARA ANÁLISE DE SADOS
Great information presented very clearly with many learning aids provided.
Gives a brief introduction of basic data analysis tools and concepts. Simple yet effective videos.
The best Data analysis course I have taken so far. Concepts are explained nicely. Interesting peer review assignments. Excellent learning experience.
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.
Sobre Programa de cursos integrados Análise e interpretação de dadosAnálise e Interpretação de Dados
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions.

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