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.
от партнера
Специализация Анализ и интерпретация данныхУэслианский университетОб этом курсе
Карьерные результаты учащихся
44%
36%
Приобретаемые навыки
Карьерные результаты учащихся
44%
36%
от партнера
Уэслианский университет
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.
Программа курса: что вы изучите
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)
Рецензии
Лучшие отзывы о курсе DATA MANAGEMENT AND VISUALIZATION
In this course we can get many ideas and opportunities of the english and the meaning of many things we used to no many things we should have been working many ideas and then how we should shall have
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.
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.
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.
Специализация Анализ и интерпретация данных: общие сведения
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions.
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Доступ к лекциям и заданиям предоставляется в зависимости от типа регистрации. Если вы проходите курс в режиме слушателя, то получите бесплатный доступ к большинству материалов курса. Чтобы открыть оцениваемые задания и возможность получить сертификат, необходимо будет приобрести прохождение с сертификатом. Это можно сделать во время прохождения в режиме слушателя или после него. Если вы не видите варианта 'Режим слушателя'.
- Курс может не предлагаться в режиме слушателя. Попробуйте бесплатную пробную версию или подайте заявку на финансовую помощь.
- Курс предлагаться в режиме 'Полный курс, без сертификата'. В нем можно просматривать все материалы, выполнять обязательные задания и получить итоговую оценку. Приобрести дополнительно прохождение с сертификатом в таком случае нельзя.
Что я получу, оформив подписку на специализацию?
Записавшись на курс, вы получите доступ ко всем курсам в специализации, а также возможность получить сертификат о его прохождении. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.
Is financial aid available?
Да, Coursera предоставляет финансовую помощь учащимся, которые не могут оплатить обучение. Чтобы подать заявление, перейдите по ссылке "Финансовая помощь" слева под кнопкой "Зарегистрироваться". Заполните форму заявления. Если его примут, вы получите уведомление. Обратите внимание: этот шаг необходимо выполнить для каждого курса специализации, в том числе для дипломного проекта. Подробнее
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