Data Collection and Analysis
What is Data Collection and Analysis?
Collecting and analyzing data is a vital part of any research project. Without data, it would be difficult to determine whether a research hypothesis is true or false. Data can be collected through a variety of methods, such as surveys, interviews, experiments, or observations. Once collected, data must be analyzed in order to draw conclusions. There are a variety of statistical methods that can be used to analyze data, such as regression analysis or ANOVA.
Data Collection and Analysis Resources
Dealing With Missing Data
This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensi...
Collect and analyze data, and communicate results.
This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and political research, official government statistics, and many other topic domains. In six courses, you will learn the basics of...
Survey Data Collection and Analytics Capstone
The Capstone Project offers qualified learners to the opportunity to apply their knowledge by analyzing and comparing multiple data sources on the same topic. Students will develop a research question, access and analyze relevant data, and critically...
Regression Modeling in Practice
Regression Modeling in Practice is course 3 of 5 in the Data Analysis and Interpretation Specialization. Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex d...
Capstone: Create Value from Open Data
The Capstone project is an individual assignment. Participants decide the theme they want to explore and define the issue they want to solve. Their “playing field” should provide data from various sectors (such as farming and nutrition, culture, econ...
Business Metrics for Data-Driven Companies
Business Metrics for Data-Driven Companies is course 1 of 5 in the Excel to MySQL: Analytic Techniques for Business Specialization. Formulate data questions, explore and visualize large datasets, and inform strategic decisions. In this Specializatio...
Modeling Risk and Realities
Useful quantitative models help you to make informed decisions both in situations in which the factors affecting your decision are clear, as well as in situations in which some important factors are not clear at all. In this course, you can learn how...
Getting and Cleaning Data
Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cov...
Practical Predictive Analytics: Models and Methods
Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical a...
Exploratory Data Analysis
This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are a...
Framework for Data Collection and Analysis
Framework for Data Collection and Analysis is course 1 of 7 in the Survey Data Collection and Analytics Specialization. This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and politi...
Managing Data Analysis
This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling...