#### Week #28 – Non-parametric Regression

Non-parametric regression methods are aimed at describing a relationship between the dependent and independent variables...

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Non-parametric regression methods are aimed at describing a relationship between the dependent and independent variables...

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June 11, 2015

A nominal scale is really a list of categories to which objects can be classified.

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June 11, 2015

The noise is the component of the observed data (e.g. of a time series) that is random and carries no useful information.

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June 11, 2015

The single linkage clustering method (or the nearest neighbor method) is a method of calculating distance between clusters in hierarchical cluster analysis .

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June 11, 2015

In a network analysis context, "edge" refers to a link or connection between two entities in a network

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June 4, 2015

The 2006 Netflix Contest has come to convey the idea of crowdsourced predictive modeling, in which a dataset and a prediction challenge are made publicly available. Individuals and teams then compete to develop the best performing model.

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June 4, 2015

The linear model is ubiquitous in classical statistics, yet real-life data rarely follow a purely linear pattern.

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May 26, 2015

Association rules, also called "market basket analysis," is a data mining method applied to transaction data.

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May 26, 2015

This week's word is actually a letter. R is a statistical computing and programming language and program, a derivative of the commercial S-PLUS program, which, in turn, was an offshoot of S from Bell Labs.

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May 19, 2015

With the advent of Big Data and data mining, statistical methods like regression and CART have been repurposed to use as tools in predictive modeling.

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April 28, 2015

The Netflix prize was a famous early application of crowdsourcing to predictive modeling.

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April 28, 2015

An A-B test is a classic statistical design in which individuals or subjects are randomly split into two groups and some intervention or treatment is applied.

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April 28, 2015

In time series forecasting, a moving average is a smoothing method in which the forecast for time t is the average value for the w periods ending with time t-1.

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March 9, 2015

In regression models, an interaction term captures the joint effect of two variables that is not captured in the modeling of the two terms individually.

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March 9, 2015

A naive forecast or prediction is one that is extremely simple and does not rely on a statistical model (or can be expressed as a very basic form of a model).

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March 9, 2015

RMSE is root mean squared error. In predicting a numerical outcome with a statistical model, predicted values rarely match actual outcomes exactly.

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March 9, 2015

A label is a category into which a record falls, usually in the context of predictive modeling. Label, class and category are different names for discrete values of a target (outcome) variable.

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March 9, 2015

A strip transect is a small subsection of a geographically-defined study area, typically chosen randomly.

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February 20, 2015

Spark is a second generation computing environment that sits on top of a Hadoop system, supporting the workflows that leverage a distributed file system.

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February 20, 2015

Bandits refers to a class of algorithms in which users or subjects make repeated choices among, or decisions in reaction to, multiple alternatives.

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February 20, 2015

In discrete response models, overdispersion occurs when there is more correlation in the data than is allowed by the assumptions that the model makes.

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January 30, 2015

In a classification model, the confusion matrix shows the counts of correct and erroneous classifications. In a binary classification problem, the matrix consists of 4 cells.

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January 30, 2015

In a classic statistical experiment, treatment(s) and placebo are applied to randomly assigned subjects, and, at the end of the experiment, outcomes are compared.

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January 16, 2015

Classification and regression trees, applied to data with known values for an outcome variable, derive models with rules like "If taxable income <$80,000, if no Schedule C income, if standard deduction taken, then no-audit."

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January 16, 2015

The predictors in a predictive model are sometimes given different terms by different disciplines. Traditional statisticians think in terms of variables.

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January 16, 2015

In logistic regression, we seek to estimate the relationship between predictor variables Xi and a binary response variable. Specifically, we want to estimate the probability p that the response variable will be a 0 or a 1.

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January 16, 2015

Bayesian statistics typically incorporates new information (e.g. from a diagnostic test, or a recently drawn sample) to answer a question of the form "What is the probability that..."

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January 16, 2015

Consider two (or more) samples subjected to different treatments. A permutation test assesses whether,

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January 9, 2015

One avid reader took issue with a recent definition of "quasi experiment." I had defined it

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January 9, 2015

In social science research, particularly in the qualitative literature on program evaluation, the term "quasi-experiment" refers to studies that do not involve the application of treatments via random assignment of subjects.

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December 5, 2014

In survey research, curb-stoning refers to the deliberate fabrication of survey interview data by the interviewer.

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December 5, 2014

Bag-of-words is a simplified natural language processing concept.

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November 7, 2014

In language processing, stemming is the process of taking multiple forms of the same word and reducing them to the same basic core form.

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November 7, 2014

Structured data is data that is in a form that can be used to develop statistical or machine learning models (typically a matrix where rows are records and columns are variables or features).

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November 7, 2014

In predictive modeling, a key step is to turn available data (which may come from varied sources and be messy) into an orderly matrix of rows (records to be predicted) and columns (predictor variables or features).

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November 7, 2014

A full Bayesian classifier is a supervised learning technique that assigns a class to a record by finding other records with attributes just like it has, and finding the most prevalent class among them.

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November 7, 2014

In computer science, MapReduce is a procedure that prepares data for parallel processing on multiple computers.

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November 7, 2014

Likert scales are categorical ordinal scales used in social sciences to measure attitude. A typical example is a set of response options ranging from "strongly agree" to "strongly disagree."

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October 10, 2014

A node is an entity in a network. In a social network, it would be a person. In a digital network, it would be a computer or device.

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October 10, 2014

Latent variable models postulate some relationship between the statistical properties of observable variables.

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October 1, 2014

K-nearest-neighbor (K-NN) is a machine learning predictive algorithm that relies on calculation of distances between pairs of records.

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October 1, 2014

The kappa statistic measures the extent to which different raters or examiners differ when looking at the same data and assigning categories.

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September 19, 2014

Censoring in time-series data occurs when some event causes subjects to cease producing data for reasons beyond the control of the investigator, or for reasons external to the issue being studied.

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September 19, 2014

Survival analysis is a set of methods used to model and analyze survival data, also called time-to-event data.

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September 18, 2014

The probability distribution for X is the possible values of X and their associated probabilities. With two separate discrete random variables, X and Y, the joint probability distribution is the function f(x,y)

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September 18, 2014

With a sample of size N, the jackknife involves calculating N values of the estimator, with each value calculated on the basis of the entire sample less one observation.

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September 18, 2014

In the interim monitoring of clinical trials, multiple looks are taken at the accruing patient results - say, response to a medication.

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September 18, 2014

A NoSQL database is distinguished mainly by what it is not -

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July 28, 2014

A similarity matrix shows how similar records are to each other.

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July 28, 2014

Predictive modeling is the process of using a statistical or machine learning model to predict the value of a target variable (e.g. default or no-default) on the basis of a series of predictor variables (e.g. income, house value, outstanding debt, etc.).

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July 28, 2014

A hold-out sample is a random sample from a data set that is withheld and not used in the model fitting process. After the model...

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July 28, 2014

Heteroscedasticity generally means unequal variation of data, e.g. unequal variance. More specifically,

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July 28, 2014

Goodness-of-fit measures the difference between an observed frequency distribution and a theoretical probability distribution which

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July 15, 2014

The geometric mean of n values is determined by multiplying all n values together, then taking the nth root of the product. It is useful in taking averages of ratios.

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July 15, 2014

Hierarchical linear modeling is an approach to analysis of hierarchical (nested) data - i.e. data represented by categories, sub-categories, ..., individual units (e.g. school -> classroom -> student).

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June 6, 2014

In medical statistics, the hazard function is a relationship between a proportion and time.

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June 6, 2014

The Fleming procedure (or *O´Brien-Fleming multiple testing procedure *) is a simple multiple testing procedure for comparing two treatments when the response to treatment is dichotomous . This procedure...

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May 30, 2014

In a directed network, connections between nodes are directional. For example..

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May 30, 2014

An adjacency matrix describes the relationships in a network. Nodes are listed in the top..

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May 30, 2014

The exponential distribution is a model for the length of intervals between two consecutive random events in time or

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May 30, 2014

Error is the deviation of an estimated quantity from its true value, or, more precisely,

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May 29, 2014

Step-wise regression is one of several computer-based iterative variable-selection procedures.

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May 16, 2014

Regularization refers to a wide variety of techniques used to bring structure to statistical models in the face of data size, complexity and sparseness.

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May 9, 2014

SQL stands for structured query language, a high level language for querying relational databases, extracting information.

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March 28, 2014

A Markov chain is a probability system that governs transition among states or through successive events.

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March 14, 2014

MapReduce is a programming framework to distribute the computing load of very large data and problems to multiple computers.

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March 14, 2014

As data processing requirements grew beyond the capacities of even large computers, distributed computing systems were developed to spread the load to multiple computers.

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March 14, 2014

The curse of dimensionality is the affliction caused by adding variables to multivariate data models.

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March 14, 2014

A data product is a product or service whose value is derived from using algorithmic methods on data, and which in turn produces data to be used in the same product, or tangential data products.

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February 21, 2014

Statistical models normally specify how one set of variables, called dependent variables, functionally depend on another set of variables, called independent variables.

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February 12, 2014

Statistical distance is a measure calculated between two records that are typically part of a larger dataset, where rows are records and columns are variables. To calculate...

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February 5, 2014

In predictive modeling, the goal is to make predictions about outcomes on a case-by-case basis: an insurance claim will be fraudulent or not, a tax return will be correct or in error, a subscriber...

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February 5, 2014

In the machine learning community, a decision tree is a branching set of rules used to classify a record, or predict a continuous value for a record. For example

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February 5, 2014

In predictive modeling, feature selection, also called variable selection, is the process (usually automated) of sorting through variables to retain variables that are likely...

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February 5, 2014

In predictive modeling, bagging is an ensemble method that uses bootstrap replicates of the original training data to fit predictive models.

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February 5, 2014

In predictive modeling, boosting is an iterative ensemble method that starts out by applying a classification algorithm and generating classifications.

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February 5, 2014

In predictive modeling, ensemble methods refer to the practice of taking multiple models and averaging their predictions.

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February 5, 2014

The expected value of a random variable, in a simple sense, is nothing but the arithmetic mean.

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December 9, 2013

Exact tests are hypothesis tests that are guaranteed to produce Type-I error at or below the nominal alpha level of the test when conducted on samples drawn from a null model.

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December 9, 2013

In statistical models, error or residual is the deviation of the estimated quantity from its true value: the greater the deviation, the greater the error.

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December 9, 2013

Endogenous variables in causal modeling are the variables with causal links (arrows) leading to them from other variables in the model.

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December 9, 2013

In a study or experiment with two groups (usually control and treatment), the investigator typically has in mind the magnitude of the difference between the two groups that he or she wants to be able to detect in a hypothesis test.

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December 9, 2013

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November 22, 2013

In a test of significance (also called a hypothesis test), Type I error is the error of rejecting the null hypothesis when it is true -- of saying an effect or event is statistically significant when it is not.

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November 22, 2013

A time series x(t); t=1,... is considered to be stationary if its statistical properties do not depend on time t .

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October 25, 2013

Data partitioning in data mining is the division of the whole data available into two or three non-overlapping sets: the training set (used to fit the model), the validation set (used to compared models), and the test set (used to predict performance on new data).

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October 25, 2013

Data mining is concerned with finding latent patterns in large databases.

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October 25, 2013

An observation´s z-score tells you the number of standard deviations it lies away from the population mean (and in which direction).

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October 25, 2013

In multivariate analysis, cluster analysis refers to methods used to divide up objects into similar groups, or, more precisely, groups whose members are all close to one another on various dimensions being measured.

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October 21, 2013

In psychology, a construct is a phenomenon or a variable in a model that is not directly observable or measurable - intelligence is a classic example.

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October 7, 2013

Collaborative filtering algorithms are used to predict whether a given individual might like, or purchase, an item.

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October 7, 2013

Longitudinal data records multiple observations over time for a set of individuals or units. A typical..

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August 20, 2013

Cross-sectional data refer to observations of many different individuals (subjects, objects) at a given time, each observation belonging to a different individual. A simple...

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August 20, 2013

Tokenization is an initial step in natural language processing. It involves breaking down a text into a series of basic units, typically words. For example...

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August 20, 2013

A natural language is what most people outside the field of computer science think of as just a language (Spanish, English, etc.). The term...

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August 20, 2013

White Hat Bias is bias leading to distortion in, or selective presentation of, data that is considered by investigators or reviewers to be acceptable because it is in the service of righteous goals.

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August 20, 2013

An edge is a link between two people or entities in a network that can be

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July 24, 2013

Stratified sampling is a method of random sampling.

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July 24, 2013

When probabilities are quoted without specification of the sample space, it could result in ambiguity when the sample space is not self-evident.

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July 24, 2013

A discrete distribution is one in which the data can only take on certain values, for example integers. A continuous distribution is one in which data can take on any value within a specified range (which may be infinite).

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July 24, 2013