Index

A

• A/B test
  • parameters, of web page / Defining A/B testing
  • conducting / Conducting an A/B test
  • experiment, planning / Planning the experiment
  • statistics, framing / Framing the statistics
  • experiment, building / Building the experiment
  • test site, building / Building the test site
  • results, viewing / Viewing the results
  • results, viewing as user / Looking at A/B testing as a user
  • results, analyzing / Analyzing the results
  • results, testing / Testing the results
• A/B testing
  • defining / Defining A/B testing
  • implementing, on server / Implementing A/B testing on the server
  • implementing / Implementing A/B testing
• adjacency list
  • about / Implementing the graphs
• alternative hypothesis
  • stating / Stating the null and alternative hypotheses
• Amazon
  • about / Improving the results
• American National Corpus (ANC) / Getting the data
• answers
  • processing / Processing the answers
  • accepted answer, predicting / Predicting the accepted answer
• Apache POI project
  • URL / Parsing the Excel files
• ArcGIS
  • about / Understanding GIS
  • working with / Working with ArcGIS
• average path length metric, social network graphs / Average path length

B

• base map
  • finding / Finding a base map
• basics, stock data modeling project
  • library, setting up / Setting up the library
  • data, obtaining / Getting the data
• Bayesian inference
  • about / Understanding null hypothesis testing
• Benford's Law
  • about / Learning about Benford's Law
  • applying, to compound interest / Applying Benford's law to compound interest
  • failing / Failing Benford's Law
  • case studies / Case studies
• between-subjects experiment design
  • about / Defining A/B testing
• betweenness centrality
  • about / Centrality
• Big Data
  • about / Getting the data
• bigrams / Preparing the data
• Bing Map
  • about / Understanding GIS
• BitTorrent
  • URL / Getting the data
• Boudewijn F. Roukema
  • URL / Case studies
• breadth-first function / Implementing the graphs, Paths
• breadth-first walk
  • about / Implementing the graphs
• burglary rates
  • about / Understanding burglary rates
  • data, obtaining / Getting the data
  • Excel files, parsing / Parsing the Excel files
  • raw data, pulling out / Pulling out raw data
  • data, exploring / Exploring the data
  • summary statistics, generating / Generating summary statistics
  • experiment, conducting / Conducting the experiment
  • results, interpreting / Interpreting the results

C

• 0.circles
  • about / Getting the data
• case studies, Benford's Law / Case studies
• centrality metric, social network graphs / Centrality
• CharSequence2TokenSequence / Loading the data into MALLET
• Class and communities in a Norwegian island parish article
  • URL / Analyzing social networks
• classification algorithms
  • error rates, calculating on / Calculating error rates
• classifier interface
  • coding / Coding the classifier interface
• classifier interface, coding
  • training / Training
  • classifying / Classifying
  • validating / Validating
• climate change, mapping
  • about / Mapping the climate change
  • data, downloading / Downloading and extracting the data
  • data, extracting / Downloading and extracting the data
  • files, downloading / Downloading the files
  • files, extracting / Extracting the files
  • data, transforming / Transforming the data – filtering
  • averages, rolling / Rolling averages
  • data, reading / Reading the data
  • sample points, interpolating / Interpolating sample points and generating heat maps using inverse distance weighting (IDW)
  • heat maps, generating with inverse distance weighting (IDW) / Interpolating sample points and generating heat maps using inverse distance weighting (IDW)
• Clojure library
  • about / Implementing the graphs
• ClojureScript
  • URL / Implementing the graphs
  • setting up / Setting up ClojureScript
  • data, visualizing with / Visualizing with D3 and ClojureScript
• ClojureScript support
  • URL / Implementing A/B testing on the server
• closeness centrality
  • about / Centrality
• clustering coefficient metric, social network graphs / Clustering coefficient
• coin tosses
  • testing / Testing coin tosses
• comma-separated values (CSV) format / Working with stock data
• Compojure
  • URL / Understanding the scaffolded site
  • about / Understanding the scaffolded site
• compound interest
  • Benford's Law, applying to / Applying Benford's law to compound interest
• conditional probability
  • about / Classifying the data
• confirmatory data analysis
  • about / Introducing confirmatory data analysis
• confusion matrix
  • about / Evaluating the outcome
• content distribution network (CDN) / Visualizing with D3 and ClojureScript
• control page / Planning the experiment
• CSV (comma-separated values) files / Preparing for visualizations
• CSV file
  • about / Getting the data
• cumulative distribution
  • about / Applying Benford's law to compound interest

D

• D3
  • URL / Visualizing the graph, Visualizing with D3 and ClojureScript, Visualizing UFO data
  • about / Setting up ClojureScript
  • data, visualizing with / Visualizing with D3 and ClojureScript
• data
  • obtaining / Getting the data, Getting the data
  • understanding, in SOTU addresses / Understanding data in the State of Union addresses
  • loading, into MALLET / Loading the data into MALLET
  • visualizing, with D3 / Visualizing with D3 and ClojureScript
  • visualizing, with ClojureScript / Visualizing with D3 and ClojureScript
• data, burglary rates
  • obtaining / Getting the data
  • exploring / Exploring the data
  • charts, generating / Generating more charts and graphs
  • graphs, generating / Generating more charts and graphs
• data analysis
  • about / Introducing confirmatory data analysis
• data classification, hoaxes
  • about / Classifying the data
  • classifier interface, coding / Coding the classifier interface
  • classifier, running / Running the classifier and examining the results
  • results, examining / Running the classifier and examining the results
• data preparation, hoaxes
  • about / Preparing the data
  • data, reading into sequence of data records / Reading the data into a sequence of data records
  • NUFORC comments, splitting out / Splitting the NUFORC comments
  • documents, categorizing based on comments / Categorizing the documents based on the comments
  • documents, partitioning into directories based on categories / Partitioning the documents into directories based on the categories
  • data, dividing into training set / Dividing them into training and test sets
  • data, dividing into test set / Dividing them into training and test sets
• degrees-between function / Degrees of separation
• degrees metric, social network graphs / Degrees
• degrees of separation metric, social network graphs / Degrees of separation
• density metric, social network graphs / Density
• depth-first walk
  • about / Implementing the graphs
• description
  • about / Description
• Dijkstra's algorithm / Paths
• dis legomena
  • about / Hapax and Dis Legomena
• double-blind experiments
  • about / Defining A/B testing

E

• 0.edges
  • about / Getting the data
• 0.egofeat
  • about / Getting the data
• Eckert IV projection / Working with map projections
• Edmunds
  • URL / Getting hotel review data
• Enclog
  • URL / Setting up the library
• enlive/html-resource function / Getting the data
• Enlive library
  • URL / Getting the data
• error rates
  • calculating, on classification algorithms / Calculating error rates
• ESRI
  • about / Understanding GIS
• experiment, A/B test
  • planning / Planning the experiment
  • building / Building the experiment
  • options, for building site / Looking at options to build the site
• experiment, burglary rates
  • conducting / Conducting the experiment
  • initial hypothesis, formulating / Formulating an initial hypothesis
  • alternative hypothesis, stating / Stating the null and alternative hypotheses
  • null hypothesis, stating / Stating the null and alternative hypotheses
  • statistical assumptions, identifying in sample / Identifying the statistical assumptions in the sample
  • tests appropriateness, determining / Determining which tests are appropriate
  • significance level, selecting / Selecting the significance level
  • critical region, determining / Determining the critical region
  • probability, calculating / Calculating the test statistic and its probability
  • test statistic, calculating / Calculating the test statistic and its probability
  • rejection, deciding for null hypothesis / Deciding whether to reject the null hypothesis or not
• exploration versus exploitation problem
  • about / Defining A/B testing
• exploratory data analysis
  • about / Introducing confirmatory data analysis
• extract-text method / Getting the data

F

• 0.feat
  • about / Getting the data
• 0.featnames
  • about / Getting the data
• Facebook
  • URL / Analyzing social networks, Understanding social network data
• facebook.tar.gz file
  • about / Getting the data
• features, GIS
  • view-shed analysis / Understanding GIS
  • topological modeling / Understanding GIS
  • hydrological modeling / Understanding GIS
  • geocoding / Understanding GIS
• feature vector functions
  • creating / Creating feature vector functions and POS tagging
• feature vectors
  • about / Creating feature vectors
  • creating / Creating feature vectors
• FileListIterator function / Loading the data into MALLET
• financial data analysis
  • about / Learning about financial data analysis
• financial modeling / Related to machine learning and market modeling in general
• First In, First Out (FIFO) queue / Implementing the graphs
• flipping coins, null hypothesis testing
  • about / Flipping coins
  • initial hypothesis, formulating / Formulating an initial hypothesis
  • null hypothesis, stating / Stating the null and alternative hypotheses
  • alternative hypothesis, stating / Stating the null and alternative hypotheses
  • statistical assumptions, identifying in sample / Identifying the statistical assumptions in the sample
  • tests appropriateness, determining / Determining appropriate tests
• force-directed layout
  • about / A force-directed layout
• frequentist approach
  • about / Understanding null hypothesis testing
• frequentist inference
  • about / Understanding null hypothesis testing
• FS library / Extracting the files
• function words / Stop lists
• future prediction, stock data modeling project
  • about / Predicting the future
  • stock prices, loading / Loading stock prices
  • news articles, loading / Loading news articles
  • training sets, creating / Creating training and test sets
  • test sets, creating / Creating training and test sets
  • best parameter, finding of neural network / Finding the best parameters for the neural network
  • neural network, training / Training and validating the neural network
  • neural network, validating / Training and validating the neural network
  • network, running on new data / Running the network on new data

G

• Gall-Peters projection / Working with map projections
• GDAL
  • URL / Understanding GIS
• geocoding
  • about / Understanding GIS
• GeoServer
  • about / Understanding GIS
  • URL / Understanding GIS
• GeoTIFF
  • about / Finding a base map
• GeoTools
  • URL / Understanding GIS
• get-edges function / Implementing the graphs
• get-index-links function / Getting the data
• GIS
  • overview / Understanding GIS
• Global Summary of the Day
  • URL / Mapping the climate change
• GNI data
  • summarizing / Summarizing World Bank land area and GNI data
• Goode homolosine projection / Working with map projections
• Google Finance
  • URL / Getting the data
• Google Map
  • about / Understanding GIS
• GPS
  • about / Understanding GIS
• graph
  • visualizing / Visualizing the graph
• graph implementation
  • data, loading / Loading the data
• graphs
  • overview / Understanding graphs
  • implementing / Implementing the graphs
• graph visualization
  • about / Visualizing the graph
  • ClojureScript, setting up / Setting up ClojureScript
  • force-directed layout / A force-directed layout
  • hive plot / A hive plot
  • pie chart / A pie chart
• gzip utility / Extracting the files

H

• H2 embedded database
  • URL / Implementing A/B testing on the server
• hapax legomena
  • about / Hapax and Dis Legomena
• heat map
  • generating, inverse distance weighting (IDW) used / Interpolating sample points and generating heat maps using inverse distance weighting (IDW)
• hive plot
  • about / A hive plot
• hoaxes
  • about / Hoaxes
  • data, preparing / Preparing the data
  • data, classifying / Classifying the data
• Homebrew
  • URL / Getting the data
• hotel review data
  • obtaining / Getting hotel review data
  • exploring / Exploring the data
  • preparing / Preparing the data
  • tokenizing / Tokenizing
  • feature vectors, creating / Creating feature vectors
  • feature vector functions, creating / Creating feature vector functions and POS tagging
  • POS tagging / Creating feature vector functions and POS tagging
  • results, cross validating / Cross-validating the results
  • experiment, running / Running the experiment
  • results, examining / Examining the results
  • results, improving / Improving the results
• HTML5 Boilerplate template
  • URL / Setting up ClojureScript
• hydrological modeling
  • about / Understanding GIS

I

• Incanter / Interpolating sample points and generating heat maps using inverse distance weighting (IDW)
  • URL / Applying Benford's law to compound interest
• Incanter library
  • URL / Implementing A/B testing
• Infochimps
  • URL / Getting the data
  • about / Getting the data
  • URL, for dataset / Getting the data
• InstanceList object
  • creating / Creating the InstanceList object
• Internet Archive
  • URL / Getting the data
• inverse distance weighting (IDW)
  • used, for generating heat maps / Interpolating sample points and generating heat maps using inverse distance weighting (IDW)
  • about / Interpolating sample points and generating heat maps using inverse distance weighting (IDW)

J

• Johnson's algorithm / Paths
• jQuery
  • URL / Visualizing with D3 and ClojureScript, Visualizing UFO data

K

• K-fold cross validation
  • about / Cross-validating the results
• knowledge-based social networks
  • about / Understanding social network data, Understanding knowledge-based social networks
  • StackExchange / Understanding social network data
  • StackOverflow / Understanding social network data
  • Quora / Understanding social network data
• Korma
  • URL / Understanding the scaffolded site
  • about / Understanding the scaffolded site

L

• LDA
  • about / Understanding data in the State of Union addresses, Understanding topic modeling
• lein-cljsbuild plugin / Setting up ClojureScript
• Leiningen 2
  • URL / Downloading the files, Implementing A/B testing on the server, Setting up the project, Setting up the library
• Leiningen 2 project.clj file
  • about / Implementing the graphs
• LIFO (Last In, First Out) queue / Implementing the graphs
• LinkedIn
  • URL / Understanding social network data
• load-topic-dists function / Visualizing with D3 and ClojureScript
• Luminus
  • about / Understanding the scaffolded site
• Luminus web framework
  • URL / Implementing A/B testing on the server

M

• machine learning / Related to machine learning and market modeling in general
• MALLET
  • data, loading into / Loading the data into MALLET
  • about / Hoaxes, Predicting the accepted answer
• map projections
  • working with / Working with map projections
• maximum entropy (maxent) classifiers
  • about / Understanding maximum entropy classifiers
• me.raynes file utility library / Implementing the graphs
• Mechanical Turk
  • URL / Preparing the data
• Mercator projection / Working with map projections
• messy data
  • dealing with / Dealing with messy data
• metrics, social network graphs
  • density / Density
  • degrees / Degrees
  • paths / Paths
  • average path length / Average path length
  • network diameter / Network diameter
  • clustering coefficient / Clustering coefficient
  • centrality / Centrality
  • degrees of separation / Degrees of separation
• monotonic function
  • about / Understanding Spearman's rank correlation coefficient

N

• naive Bayesian classifiers
  • about / Understanding naive Bayesian classifiers
• network diameter metric, social network graphs / Network diameter
• networking-oriented social networks
  • about / Understanding social network data
  • Facebook / Understanding social network data
  • LinkedIn / Understanding social network data
  • Twitter / Understanding social network data
  • Sina Weibo / Understanding social network data
• neural nets
  • text, analyzing / Analyzing both text and stock features together with neural nets
  • stock features, analyzing / Analyzing both text and stock features together with neural nets
  • about / Understanding neural nets
  • setting up / Setting up the neural net
  • training / Training the neural net
  • running / Running the neural net
  • validating / Validating the neural net
  • best parameters, finding / Finding the best parameters
• news articles
  • working with / Working with news articles
  • loading / Loading news articles
• noir
  • about / Understanding the scaffolded site
  • URL / Understanding the scaffolded site
• NUFORC
  • URL / Splitting the NUFORC comments
• NUFORC comments
  • splitting out / Splitting the NUFORC comments
• null-hypothesis test
  • about / Framing the statistics
• null hypothesis
  • stating / Stating the null and alternative hypotheses
• null hypothesis process
  • using / Understanding the process
  • initial hypothesis, formulating / Formulating an initial hypothesis
  • tests appropriateness, determining / Determining appropriate tests
  • significance level, selecting / Selecting the significance level
  • critical region, determining / Determining the critical region
  • probability, calculating / Calculating the test statistics and its probability
  • test statistic, calculating / Calculating the test statistics and its probability
  • rejection, deciding / Deciding whether to reject the null hypothesis or not
• null hypothesis testing
  • about / Introducing confirmatory data analysis, Understanding null hypothesis testing
  • flipping coins / Flipping coins

O

• online-controlled experiments
  • about / Defining A/B testing
• Open ANC (OANC)
  • about / Getting the data
  • URL / Getting the data
• OpenNLP library
  • URL / Tokenizing
• OpinRank Review dataset
  • URL / Getting hotel review data

P

• p-value
  • about / Introducing confirmatory data analysis
• Pareto Principle
  • about / Introducing the 80/20 rule
• part-of-speech annotated unigrams / Preparing the data
• partition-all function
  • about / Cross-validating the results
• partition-spread function
  • about / Cross-validating the results
• partition function
  • about / Cross-validating the results
• paths metric, social network graphs / Paths
• perform-test function
  • about / Viewing the results
• pie chart / A pie chart
• POS
  • about / Creating feature vector functions and POS tagging
• POS tagging / Creating feature vector functions and POS tagging
• prior or assumed probability / Classifying the data
• process-speech-page function / Getting the data
• project
  • setting up, for topic modeling / Setting up the project

Q

• Quantum GIS
  • about / Understanding GIS
  • URL / Understanding GIS
• quintiles
  • about / Matching the 80/20 rule
• Quora
  • URL / Understanding social network data, Understanding knowledge-based social networks

R

• 80/20 rule
  • about / Introducing the 80/20 rule
  • data, obtaining / Getting the data
  • looking, at data amount / Looking at the amount of data
  • looking, at data format / Looking at the data format
  • data, defining / Defining and loading the data
  • data, loading / Defining and loading the data
  • frequencies, counting / Counting frequencies
  • data, sorting / Sorting and ranking
  • data, ranking / Sorting and ranking
  • patterns, finding of participation / Finding the patterns of participation
  • matching / Matching the 80/20 rule
• random-controlled experiments
  • about / Defining A/B testing
• ranks, combining
  • about / Combining ranks
  • looking at those who only post questions / Looking at those who only post questions
  • looking at those who only post answers / Looking at those who only post answers
  • looking at those who post both questions and answers / Looking at those who post both questions and answers
• raw data, burglary rates
  • about / Pulling out raw data
  • data tree, building / Growing a data tree
  • data tree, cutting down / Cutting down the data tree
  • implementing / Putting it all together
  • data, transforming / Transforming the data
  • data sources, joining / Joining the data sources
  • data, pivoting / Pivoting the data
  • missing data, filtering / Filtering the missing data
  • wrapper function, creating / Putting it all together
• read-eval-print loop (REPL) / Loading the data
• reducers / Reading the data
• results, A/B test
  • viewing / Viewing the results
  • viewing, as user / Looking at A/B testing as a user
  • analyzing / Analyzing the results
  • testing / Testing the results
• results, burglary rates
  • interpreting / Interpreting the results
• results, hotel review data
  • cross validating / Cross-validating the results
  • examining / Examining the results
  • error rates, combining / Combining the error rates
  • improving / Improving the results

S

• scaffolded site
  • about / Understanding the scaffolded site
• select-keys function
  • about / Implementing A/B testing
• Selmer
  • about / Understanding the scaffolded site
  • URL / Understanding the scaffolded site
• sentiment analysis
  • overview / Understanding sentiment analysis
• server
  • A/B testing, implementing on / Implementing A/B testing on the server
• Simple Logging Facade for Java library
  • URL / Implementing the graphs
  • about / Implementing the graphs
• Sina Weibo
  • URL / Understanding social network data
• single-blind experiments
  • about / Defining A/B testing
• Six Degrees of Kevin Bacon game
  • about / Analyzing social networks
• Slate
  • URL / Getting the data
• social data participation analysis project
  • about / Setting up the project
  • analyses, understanding / Understanding the analyses
  • social network data, understanding / Understanding social network data
  • knowledge-based social networks, understanding / Understanding knowledge-based social networks
  • 80/20 rule, introducing / Introducing the 80/20 rule
  • 80/20 rule, matching / Matching the 80/20 rule
  • looking, for 20 percent of questioners / Looking for the 20 percent of questioners
  • looking, for 20 percent who answer questions / Looking for the 20 percent of respondents
  • ranks, combining / Combining ranks
  • up-voted answers, finding / Finding the up-voted answers
  • answers, processing / Processing the answers
  • setting up / Setting up
  • InstanceList object, creating / Creating the InstanceList object
  • training sets / Training sets and Test sets, Training
  • test sets / Training sets and Test sets, Testing
  • outcome, evaluating / Evaluating the outcome
• social network graphs
  • measuring / Measuring social network graphs
• social networks
  • analyzing / Analyzing social networks
• SOTU
  • about / Understanding data in the State of Union addresses
• SOTU address
  • data, understanding / Understanding data in the State of Union addresses
  • about / Understanding data in the State of Union addresses
  • graph, for increase in word count / Understanding data in the State of Union addresses
• Spearman's rank correlation coefficient
  • about / Understanding Spearman's rank correlation coefficient
• StackExchange
  • URL / Understanding social network data
  • URL, for periodic data dump / Getting the data
• StackOverflow
  • URL / Understanding social network data
  • front page / Understanding knowledge-based social networks
• Stanford Large Network Dataset Collection
  • about / Getting the data
  • URL / Getting the data
• statistics, A/B test
  • framing / Framing the statistics
• stock data
  • working with / Working with stock data
• stock data modeling
  • data, preparing / Getting prepared with data
  • working, with news articles / Working with news articles
• stock data modeling project
  • basics, setting up / Setting up the basics
  • text, analyzing / Analyzing the text
  • stock prices, inspecting / Inspecting the stock prices
  • text, and stock features merging / Merging text and stock features
  • text, analyzing with neutral nets / Analyzing both text and stock features together with neural nets
  • stock features analyzing with neutral nets / Analyzing both text and stock features together with neural nets
  • future, predicting / Predicting the future
  • weakness / Related to this project
• stock features
  • analyzing, with neural nets / Analyzing both text and stock features together with neural nets
• stock prices
  • inspecting / Inspecting the stock prices
  • loading / Loading stock prices
• stop lists / Stop lists
• subdirectories, Luminus project
  • resources / Understanding the scaffolded site
  • src / Understanding the scaffolded site
  • src/web_ab/models/ / Understanding the scaffolded site
  • src/web_ab/routes/ / Understanding the scaffolded site
  • src/web_ab/views/templates/ / Understanding the scaffolded site
  • test/web_ab/test/ / Understanding the scaffolded site
• sum of squared errors (SSE)
  • about / Validating the neural net

T

• ?Torrent
  • URL / Getting the data
• t-test
  • overview / Understanding the t-test
  • coin tosses, testing / Testing coin tosses
• t-test function
  • about / Implementing A/B testing
• tab-separated values (TSV)
  • about / Preparing the data
• test-on utility
  • about / Validating the neural net
• test page / Planning the experiment
• tests appropriateness, flipping coins
  • significance level, selecting / Selecting the significance level
  • critical region, determining / Determining the critical region
  • test statistic, calculating / Calculating the test statistic and its probability
  • probability, calculating / Calculating the test statistic and its probability
  • rejection, deciding for null hypothesis / Deciding whether to reject the null hypothesis or not
• test site, A/B test
  • building / Building the test site
• text
  • analyzing, with neural nets / Analyzing both text and stock features together with neural nets
• text, and stock features
  • merging / Merging text and stock features
• text, stock data modeling project
  • graph, viewing of frequencies / Hapax and Dis Legomena
• text analysis, stock data modeling project
  • about / Analyzing the text
  • vocabulary, analyzing / Analyzing vocabulary
  • stop lists / Stop lists
  • graph, viewing of frequencies / Hapax and Dis Legomena
  • hapax legomena / Hapax and Dis Legomena
  • dis legomena / Hapax and Dis Legomena
  • TF-IDF / TF-IDF
• tf-idf
  • about / Analyzing the text
• TF-IDF
  • about / TF-IDF
• tf-idf-freqs function / TF-IDF
• tokenizing / Tokenizing
  • about / Analyzing vocabulary
• TokenSequence2FeatureSequence / Loading the data into MALLET
• TokenSequenceLowercase / Loading the data into MALLET
• TokenSequenceRemoveStopwords / Loading the data into MALLET
• tools, for GIS specialists
  • ArcGIS / Understanding GIS
  • Quantum GIS / Understanding GIS
  • GeoServer / Understanding GIS
  • GDAL / Understanding GIS
  • GeoTools / Understanding GIS
• topic 26
  • exploring / Exploring topic 26
• topic 42
  • exploring / Exploring topic 42
• topic 43
  • exploring / Exploring topic 43
• topic model
  • about / Understanding topic modeling
• topic modeling
  • overview / Understanding topic modeling
  • URLs, for articles / Understanding topic modeling
  • project, setting up for / Setting up the project
• topic modeling descriptions
  • about / Topic modeling descriptions
• topics
  • exploring / Exploring the topics
• topological modeling
  • about / Understanding GIS
• trigrams / Preparing the data
• TripAdvisor
  • URL / Getting hotel review data
• TSV file
  • about / Getting the data
• Twitter
  • URL / Understanding social network data
• type one error
  • about / Testing the results

U

• UFO data
  • visualizing / Visualizing UFO data
• UFO sightings
  • data, obtaining / Getting the data
  • data, extracting / Extracting the data
  • dealing, with messy data / Dealing with messy data
• unigrams / Preparing the data
• United Nations Office on Drugs and Crime
  • URL / Getting the data
• UNODC crime data
  • summarizing / Summarizing UNODC crime data
• up-voted answers
  • finding / Finding the up-voted answers
• US National Oceanic and Atmospheric Administration (NOAA) / Mapping the climate change
• US Topo Maps / Working with ArcGIS

V

• view-shed analysis
  • about / Understanding GIS
• visualizations
  • preparing for / Preparing for visualizations
• vocabulary
  • analyzing / Analyzing vocabulary

W

• Weka, and cross validation
  • connecting / Connecting Weka and cross-validation
• Weka machine learning library
  • URL / Tokenizing, Using the Weka machine learning library
  • using / Using the Weka machine learning library
• when-is-over function
  • about / Viewing the results
• World Bank land area
  • summarizing / Summarizing World Bank land area and GNI data
• World DataBank
  • URL / Looking at the world population data
  • downloading / Looking at the world population data
• world population data
  • viewing / Looking at the world population data

Y

• Yahoo Answers
  • URL / Understanding knowledge-based social networks

Z

• 7-zip site
  • URL / Getting the data