Oct 31st 2016

Data Analysis Tools (Coursera)

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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.

Data Analysis Tools is course 2 of 5 in the Data Analysis and Interpretation Specialisation.

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 and techniques, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python (including, but not limited to, the popular pandas and Scikit-learn python libraries). Throughout the Specialization, you will analyze a research question of your choice and summarize your insights. In the final 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 partner, DRIVENDATA, to help them solve some of the world's biggest social challenges by joining one of their competitions. Regular feedback from peers will provide you a chance to shape your question in new ways. 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 guidance about using data, or you just have some burning questions you want to explore. No prior experience is required, but by the end you will have mastered analytical methods and applications to conduct original research that can inform complex decisions.


Week 1: Hypothesis Testing and ANOVA

Week 2: Chi Square Test of Independence

Week 3: Pearson Correlation

Week 4: Exploring Statistical Interactions