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SAS Global Forum Scholarship Program. Notes 7a Chi-square Goodness-of-fit. Chi-Square ( 2 ) Goodness-of-Fit The Z-test, t-test, and Pearson's r all assume that at least one of the variables (usually the dependent variable) is measured on the interval or ratio scale.

Notes 7a Chi-square Goodness-of-fit

When variables of interest are nominal or categorical, these statistical tests could be inappropriate and produce misleading information. A chi-square statistic, however, provide a more appropriate assessment for such data. Rethinking Business Models for Online Higher Education. We’re beginning to see real change in higher education.

Rethinking Business Models for Online Higher Education

Not just incremental, “around the edges” change, but substantive and inspiring. No, I’m not referring the first wave of MOOCs. These early efforts at MOOCs amounted to little more than promotional vehicles for elite universities that don’t need promotion, and innovation from institutions with the least to gain from change in higher education. Rather, I’m thinking here of initiatives like ASU’s Global Freshman Academy, the sincere interest in competency-based education which, if done right, requires a substantial modification to current practices, new kinds of partnerships between education companies and colleges, and Minerva University, which blends location and online in new ways.

Each of these represents an example of business model innovation. Higher Education’s Overarching Business Model The concept of business models can be used to help us more clearly see understand how our institution is organized and how it operates. Channels.

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RDataMining.com: R and Data Mining. Data. When To Use Supervised And Unsupervised Data Mining » When To Use Supervised And Unsupervised Data Mining Data mining techniques come in two main forms: supervised (also known as predictive or directed) and unsupervised (also known as descriptive or undirected).

When To Use Supervised And Unsupervised Data Mining »

Both categories encompass functions capable of finding different hidden patterns in large data sets. Although data analytics tools are placing more emphasis on self service, it’s still useful to know which data mining operation is appropriate for your needs before you begin a data mining operation. Research Blog: Text summarization with TensorFlow.

Original Text: Alice and Bob took the train to visit the zoo.

Research Blog: Text summarization with TensorFlow

They saw a baby giraffe, a lion, and a flock of colorful tropical birds. Extractive Summary: Alice and Bob visit the zoo. saw a flock of birds. Above we extract the words bolded in the original text and concatenate them to form a summary. As we can see, sometimes the extractive constraint can make the summary awkward or grammatically strange. Another approach is to simply summarize as humans do, which is to not impose the extractive constraint and allow for rephrasings. SQLCourse - Lesson 1: What is SQL? Corpora for Language Learning and Teaching.

Machine learning based tools

Chapter6h. Cuttlefish - Network visualization and workbench. SocioViz is a free Social Network Analysis tool for Twitter. Do you need a social media analytics software for Social Media Marketing, Digital Journalism or Social Research? Have a try and jump on board! Social Network Analysis. Brief Description: "Social network analysis is the mapping and measuring of relationships and flows between people, groups, organisations, computers or other information/knowledge processing entities.

Social Network Analysis

" (Valdis Krebs, 2002). Social Network Analysis (SNA) is a method for visualizing our people and connection power, leading us to identify how we can best interact to share knowledge. A related practice is Network Mapping. History: When to use: How to use: From the UK's NHS KM Library: "In the context of knowledge management, social network analysis (SNA) enables relationships between people to be mapped in order to identify knowledge flows: who do people seek information and knowledge from? Informal Face to Face Network Mapping To highlight the value of our social networks, at a face to face gathering create an informal map using Post-it notes on a large piece of paper. 20+ Free and Open Source Social Network Analysis Software - Butler Analytics. Social network analysis software generally uses network and graph theory to investigate social structures both analytically and visually.

20+ Free and Open Source Social Network Analysis Software - Butler Analytics

The main constructs are nodes (the entities we are interested in – typically people), and the ties or edges that connect them. Many of the products listed here are open source with a license that permits free use in commercial settings. Cuttlefish is a network workbench application that visualizes the networks with some of the best known layout algorithms. Top 30 Social Network Analysis and Visualization Tools. Here is a list of top Social Network Analysis and Visualization Tools we found – see also KDnuggets Social Network Analysis, Link Analysis, and Visualization page.

Top 30 Social Network Analysis and Visualization Tools

Centrifuge offers analysts and investigators an integrated suite of capabilities that can help them rapidly understand and glean insight from new data sources, visualize discoveries by interacting with data, collaborate to draw conclusions. Commetrix is a Software Framework for Dynamic Network Visualization and Analysis that supports Community Moderators, Members, and Network Researchers.

Commetrix is an exploratory analysis tool for dynamic network data. Its connectors can conveniently read all sources of accessible network data, like co-authorship or business process networks. Software metric. A software metric is a standard of measure of a degree to which a software system or process possesses some property.

Software metric

Even if a metric is not a measurement (metrics are functions, while measurements are the numbers obtained by the application of metrics), often the two terms are used as synonymous. Since quantitative measurements are essential in all sciences, there is a continuous effort by computer science practitioners and theoreticians to bring similar approaches to software development. The goal is obtaining objective, reproducible and quantifiable measurements, which may have numerous valuable applications in schedule and budget planning, cost estimation, quality assurance testing, software debugging, software performance optimization, and optimal personnel task assignments.

Common software measurements[edit]

Cohesion metric tool

Predictive Analytics. TOPIC MODELING. IBM Watson Developer Cloud. Training Videos.