Participants in this course will learn why Bayesian computing has gained wide popularity, and how to apply Markov Chain Monte Carlo techniques (MCMC) to Bayesian statistical modeling using WinBUGS software.
In this online course you will learn you how to apply predictive modeling methods, and persuasion (uplift) models in particular. The focus will be on targeting voters in political campaigns.
Meta-Analysis refers to the statistical analyses that are used to synthesize summary data from a series of studies. This course covers some advanced issues in meta-analysis. Participants should have completed the basic course in meta-analysis or an equivalent.
Try out our introductory statistics series for one week - you can learn stats!
The course introduces the use of mathematical models for managerial decision making and covers how to formulate linear programming models for decision problems where multiple decisions need to be made in the best possible way while simultaneously satisfying a number of logical conditions (or constraints). You will learn how to use spreadsheet software to implement and solve these linear programming problems.
This course will provide the basics of vector and matrix algebra and operations necessary to understand multivariate statistical methods, including the notions of the matrix inverse, generalized inverse and eigenvalues and eigenvectors.
Rasch analysis constructs linear measures from scored observations, such as responses to multiple-choice questions, Likert scales and quality-of-life assessments. This course covers the practical aspects of data setup, analysis, output interpretation, fit analysis, differential item functioning, dimensionality and reporting.
This course will teach a mix of quantitative and qualitative methods for describing, measuring and analyzing social networks.
This course covers the crafting of survey questions, the design of surveys, and different sampling procedures that are used in practice. Longstanding basic principles of survey design are covered, and the impact of the trend toward increased respondent resistance is discussed.
This course, the second in a three-course sequence, provides an easy introduction to inference and association through a series of practical applications, based on the resampling/simulation approach.
To provide an easy introduction to statistical inference for a single variable.
This course covers sensitivity-specificity and predictive values of medical tests, confidence intervals, medical vs. statistical significance, and chi-square, Student's t and ANOVA F-tests, including multiple comparisons.
This course covers sensitivity-specificity and predictive values of medical tests, confidence intervals, medical vs. statistical significance, and chi-square, Student's t and ANOVA F-tests, including multiple comparisons.
Logistic regression extends ordinary least squares (OLS) methods to model data with binary (yes/no, success/failure) outcomes. Rather than directly estimating the value of the outcome, logistic regression allows you to estimate the probability of a success or failure.
This course will explain meta analysis - the methods that are used to assess multiple statistical studies on the same subject and draw conclusions.
This course is designed to give you an introduction to the algorithms, techniques and software used in natural language processing (NLP).
This course will teach you how to choose an appropriate time series
forecasting method, fit the model, evaluate its performance, and
use it for forecasting.
This course is about the interactive exploration of data, and how it is achieved using state-of-the-art data visualization software.
This course will show you how to use R to create statistical models and use them to analyze data.
In this online course, "Programming 2:Python," you'll learn
everything you need to get you started using Python for data analysis. We'll review basic Python skills and data structures, move on to how
to load data from different sources, rearrange and aggregate it, and
finally how to analyze and visualize it to create high-quality products.