Introduction to Social Network Analysis (SNA)

Social Network Analysis has existed for a long time, but social media has fundamentally changed the way we do this analysis. Data has become more plentiful and easy to collect, but this has pushed the boundaries of existing techniques. Sociological methods do not easily scale to the size of these networks, but purely statistical methods miss the complex social interactions that take place. This course will teach a mix of quantitative and qualitative methods for describing, measuring and analyzing social networks. We will learn how to identify influential individuals, track the spread of information through networks, and see how to use these techniques on real problems.

Dr. Jennifer Golbeck will present his course “Introduction to Social Network Analysis (SNA)” online at Statistics.com. For more details please visit at Social Network Analysis.

Who Should Take This Course:

Anyone who wants to learn to analyze social data - people who work in organizations with social media presences that they want to manage and analyze, or those who work on these networks and want to better understand the details of the environment they create.

Course Program:

Course outline: The course is structured as follows

WEEK 1:  Network Analysis Basics

·         Basic Terminology

·         Metrics

·         Visualization

WEEK 2:  The Social Network

·         Tie strength

·         Trust - User attributes and behavior

WEEK 3:  Analytics

·         Modeling

·         Sampling

·         Content Analysis

·         Propagation

WEEK 4:  Applications

·         Location

·         Filtering and recommender systems

·         Business use

Dr. Jennifer Golbeck, instructor, is Director of the Human-Computer Interaction Lab and an Associate Professor in the College of Information Studies at the University of Maryland, College Park. She is a Research Fellow of the Web Science Research Initiative and in 2006, she was selected as one of IEEE Intelligent Systems' Top Ten to Watch, a list of their top young AI researchers.

You will be able to ask questions and exchange comments with the instructors via a private discussion board throughout the course.   The courses take place online at statistics.com in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

Email: info@c-elt.com

Call: 020 66009116

Websites:

www.india.statistics.com

www.c-elt.com

Biostatistics 1

Karl Pearson founded the journal "Biometrika" 110 years ago, and laid the foundation for today's classical biostatistics (chi-square test, hypothesis testing, correlation, more).  His political views, even for the times, were unsavory (a proponent of eugenics, he advocated "war against the inferior races"), but his statistical contributions remain embedded in the technical and pedagogical literature.  Statistics.com offers a two-course online sequence in Biostatistics, starting with Biostatistics 1 and Biostatistics 2. Each course is 4 weeks long, and taught by Prof. Abhaya Indrayan, co-author of "Medical Biostatistics." For more details please visit at Biostatistics 1.

"Biostatistics 1" 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.

Who Should Take This Course:

This non-mathematical course is specially designed for medical and health professionals who deal with medical data and want to acquire some statistical skills. These include nursing, pharmacy, laboratory technology and nutrition professionals beside physicians, surgeons and dentists.

Course Program:

Course outline: The course is structured as follows

SESSION 1: Probability in Health and Medicine

• Medical uncertainties and probability
• Elementary laws of probability
• Bayes' Rule
• Sensitivity-specificity of a medical test
• Positive and negative predictive value
• Effect of prevalence

SESSION 2: Confidence Intervals

• Sampling distributions and SEs
• Large sample CI for one-sample mean and proportion
• Exact CI for proportion and median
• Large sample CI for differences between means and proportions
• Sample size for estimation

SESSION 3: Statistical vs. Medical Significance

• P-value and level of significance
• The concept of statistical power
• Medical vs. statistical significance
• Sample size for significance and power analysis
• Chi-square test for simple situations

SESSION 4: Some Statistical Tests for Quantitative Data

• Student's t-test for one-sample and two-sample situations
• ANOVA for one-way and two-way tables
• Tukey test and Bonferroni procedures for multiple comparisons
• Test for medically significant gain and equivalence test

Dr. Abhaya Indrayan, in addition to authoring "Medical Biostatistics," (2nd ed., CRC Press), has also written a book on medical research methods.  He is Chair of the Department of Biostatistics and Medical Informatics at the College of Medical Sciences, University of Delhi, and frequently provides biostatistical Consultation to the World Health Organization, the World Bank and UNAIDS.

You will be able to ask questions and exchange comments with the instructors via a private discussion board throughout the course.   The courses take place online at statistics.com in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

Email: info@c-elt.com

Call: 020 66009116

Websites:

www.india.statistics.com

www.c-elt.com

Many-Facet Rasch Measurement

Online course “Many-Facet Rasch Measurement” will  cover the analysis and interpretation of judge-intermediated ratings, like essay grading, Olympic ice-skating, therapist ratings of patient behavior, etc. Specifically, you will learn how to assess whether raters function (as desired) interchangeably, or whether they differ systematically in ways that can impair the overall rating system.

Dr. Everett V. Smith, Jr will present his course “Many-Facet Rasch Measurement” online at Statistics.com. For more details please visit at Many-Facet Rasch Measurement.

Who can take this course:

Researchers and analysts in education, psychology, medicine and other fields who deal with data that include ratings from human judges.

Course Program:

Course outline: The course is structured as follows

WEEK 1: Software Operation and Basic Concepts

• Software installation and operation
• Facets, elements, persons, items, raters
• Data entry methods, including using Excel
• Rasch measurement concepts
• Dichotomous and polytomous models
• Rasch measures and measurement rulers

WEEK 2: Fit Analysis and Measurement Models

• A two-facet dichotomous analysis
• Observations, measures, expectations and residuals
• Mean-square and standardized fit statistics
• Outfit and Infit statistics
• A three-facet polytomous analysis
• Reliability, separation and inter-rater reliability
• Rating scale structures

WEEK 3: Estimation and Interactions

• A four-facet polytomous analysis
• Missing data
• Bias/interaction analysis
• Graphing interactions with Excel
• Recoding the data
• Interactions with dummy facets

WEEK 4: Anchoring

• Subset detection and remedies
• Anchoring, linking and equating
• Judging plan and Generalizability Theory
• Prettifying output for communication

The instructor is, Dr. Everett V. Smith Jr., Professor of Educational Psychology at the University of Illinois at Chicago, and co-editor of "Introduction to Rasch Measurement: Theory, Models, and Applications," "Rasch Measurement: Advanced and Specialized Applications," and more. He serves as the Associate Editor for the "Journal of Applied Measurement" and is on the editorial boards of "Educational and Psychological Measurement" and the "Journal of Nursing Measurement."

You will be able to ask questions and exchange comments with the instructors via a private discussion board throughout the course.   The courses take place online at statistics.com in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

Email: info@c-elt.com

Call: 020 66009116

Websites:

www.india.statistics.com

www.c-elt.com

Visualization in R with ggplot2

"Plot," meaning a piece of land, came from Old English (origin around 1100), and soon gave rise to the "graph" meaning of the term.  The term "ggplot" comes from Leland Wilkinson's book "Grammar of Graphics," and refers to an R Project that codifies and implements "best practices" in graphing.  Dr. Randall Pruim will present his course "Visualization in R with ggplot2," online at statistics.com. For more details please visit at Visualization in R with ggplot2.

In "Visualization in R with ggplot2", you will learn how to use the ggplot R Project to make, format, label and adjust graphs using R.  The "grammar of graphics" for which ggplot is named is a system of describing and organizing the fundamental components of a graph and the process of creating a graph.  Using ggplot2, participants will learn how to design and implement graphs in an efficient, elegant and systematic manner, following principles of general good graphing practice.

Who can take this course:

Statistical analysts who use R and need to create or modify graphs.

Course Program:

Course outline: The course is structured as follows

SESSION 1: Introduction to ggplot2

• How to create basic plots (scatterplots, histograms, and barcharts) using qplot()
• Setting vs. mapping

• How to add extra variables with aesthetics (like color, shape, and size) or faceting

SESSION 2: Finer control over plots

• The ggplot system: geoms, stats, and all that jazz
• How to display data in other forms (densityplots, boxplots, etc.) using geoms
• Techniques for overcoming overplotting with drawing scatterplots of large datasets

SESSION 3: Transformations

• Group-wise summaries and transformations to add extra information to your plots
• How to visualize time series

SESSION 4: Polishing Your Plots

• Tweaking your plots for maximum presentation impact
• Introduction to color theory
• Labels, legends, and axes

• Using and adjusting the plot themes

Dr. Randall Pruim is chair of Mathematics and Statistics department at Calvin College as well as director of the Calvin’s Integrated Science Research Institute (ISRI), which was founded in 2008 through a $1.1 million grant from the Howard Hughes Medical Institute. Dr. Pruim is also part of Project MOSAIC, an NSF-funded initiative to improve the teaching of modeling, statistics, calculus, and computation nationally. The mosaic R package, available on CRAN, is a product of Project MOSAIC that makes it easier to teach calculus and statistics using R.

This course takes place over the internet at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. The course typically requires 15 hours per week. Course participants will be given access to a private discussion board so that they will be able to ask questions and exchange comments with instructor, Dr. Randall Pruim. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

For More details contact at

Email: info@c-elt.com

Call: 020 6600 9116

Websites:

www.india.statistics.com

www.c-elt.com