Whether being used to customize advertising to millions of website visitors or streamline inventory ordering at a small restaurant, data is becoming more integral to success. Too often, we’re not sure how use data to find answers to the questions that will make us more successful in what we do. In this course, you will discover what data is and think about what questions you have that can be answered by the data – even if you’ve never thought about data before. Based on existing data, you will learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly. By the end of the course, you will be able to use powerful data analysis tools – either SAS or Python – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs. Throughout the course, you will share your progress with others to gain valuable feedback, while also learning how your peers use data to answer their own questions.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Data Analysis and Interpretation
von
Spezialisierung Data Analysis and InterpretationWesleyan UniversityÜber diesen Kurs
Karriereergebnisse der Lernenden
44%
36%
Kompetenzen, die Sie erwerben
Karriereergebnisse der Lernenden
44%
36%
von
Wesleyan University
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.
Lehrplan - Was Sie in diesem Kurs lernen werden
Selecting a research question
We would like to welcome you to Wesleyan University's Data Analysis and Interpretation Specialization. In this session, we will discuss the basics of data analysis. Your task will be to select a data set that you would like to work with and to review available code books that help you develop your own research question. You will also set up a Tumblr blog that will allow you to reflect on these experiences, submit assignments and share your work with others throughout the course. First, you may want to check out the welcome video
Writing your first program - SAS or Python
In this session, we will discuss how to write a basic program that allows you to load a data set and examine frequency distributions. Your task will be to write a program that helps you to explore the variables you have selected for your own research question. You may choose either Python or SAS. Both are made freely available, and we have created a helpful guide to support you in making the decision. Once you have selected your platform, just follow the instructions in the appropriate "GETTING STARTED...." file, and then check out this week's video lessons aimed at helping you write and run your first program. You need only view the lessons for one of the statistical platforms (SAS or Python).
Managing Data
In this session, we will help you to make and implement even more decisions with data. Statisticians often call this task 'data management', while computer scientists like the term 'data munging'. Whatever you call it, it is a vital and ongoing process when working with data. Your task will be to write a program that manages the variables you have selected for your own research question.
Visualizing Data
In this session we will discuss descriptive statistics and get you visualizing your newly data managed variables individually and as graphs showing the relationships between them.
Supplemental Materials (All Weeks)
Bewertungen
Top-Bewertungen von DATA MANAGEMENT AND VISUALIZATION
This is a great course for beginners. The course instructors have arranged the course at a very comfortable pace and this is a great beginning point for anyone who wants to learn SAS or Python.
This course covers the basic data management and visualization using SAS and Python. I like the simplicity and straightforwardness of the contents. Will continue to explore this specialization.
Great introduction to quantitative data analysis and a great refresher for those of us who have been out of it for a while. Presented well, the videos were great, and I enjoyed it very much.
I learnt a lot from this course in data management and visualization and enjoyed the assignment parts of the course. I also gained insights in making data management decisions!
Über den Spezialisierung Data Analysis and Interpretation
Häufig gestellte Fragen
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
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