Q research software
Encyclopedia
Q research software is computer software
for the analysis of market research data. Launched in 2007, Q is developed by Numbers International Pty Ltd.
.
formats (Office 2000, 2002, 2003, 2007 and 2010) using Office templates. Additionally, Q exports tables and charts as PDFs, and it exports data in comma-separated values
(.csv) and SPSS (.sav) formats.
and Excel-style formulas.
, Principal Components Analysis
, Latent class analysis, mixture models (mixtures of constrained normal distributions), K-means cluster analysis, Correspondence analysis
and Multiple correspondence analysis
.
).
Q.2 - April 2008
Q.3 - February 2009
Q.4 - October 2010
Computer software
Computer software, or just software, is a collection of computer programs and related data that provide the instructions for telling a computer what to do and how to do it....
for the analysis of market research data. Launched in 2007, Q is developed by Numbers International Pty Ltd.
Interactive data analysis
Q implements an interactive approach to data analysis, whereby most standard manipulations are done by dragging and dropping (e.g., NETs and SUMs are computed by dragging and dropping rows on a table). The program is designed according to the principles of data reductionData reduction
Data Reduction is the transformation of numerical or alphabetical digital information derived empirical or experimentally into a corrected, ordered, and simplified form....
.
Graphics
Q exports tables and charts in native Microsoft OfficeMicrosoft Office
Microsoft Office is a non-free commercial office suite of inter-related desktop applications, servers and services for the Microsoft Windows and Mac OS X operating systems, introduced by Microsoft in August 1, 1989. Initially a marketing term for a bundled set of applications, the first version of...
formats (Office 2000, 2002, 2003, 2007 and 2010) using Office templates. Additionally, Q exports tables and charts as PDFs, and it exports data in comma-separated values
Comma-separated values
A comma-separated values file stores tabular data in plain-text form. As a result, such a file is easily human-readable ....
(.csv) and SPSS (.sav) formats.
Creating variables
Coding of text data, construction of numeric and categorical variables using JavaScriptJavaScript
JavaScript is a prototype-based scripting language that is dynamic, weakly typed and has first-class functions. It is a multi-paradigm language, supporting object-oriented, imperative, and functional programming styles....
and Excel-style formulas.
Advanced analysis
Multiple regression, including Binary logit, Ordered logit, Multinomial logit, Regression trees, Classification trees, choice modelling (choice, rankings, ratings, best-worst, availability designs), Max-DiffMaxDiff
Maximum difference scaling is a discrete choice model first described by Jordan Louviere in 1987 while on the faculty at the University of Alberta. The first working papers and publications occurred in the early 1990s...
, Principal Components Analysis
Principal components analysis
Principal component analysis is a mathematical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of uncorrelated variables called principal components. The number of principal components is less than or equal to...
, Latent class analysis, mixture models (mixtures of constrained normal distributions), K-means cluster analysis, Correspondence analysis
Correspondence analysis
Correspondence analysis is a multivariate statistical technique proposed by Hirschfeld and later developed by Jean-Paul Benzécri. It is conceptually similar to principal component analysis, but applies to categorical rather than continuous data...
and Multiple correspondence analysis
Multiple correspondence analysis
In statistics, multiple correspondence analysis is a data analysis technique for nominal categorical data, used to detect and represent underlying structures in a data set. It does this by representing data as points in a low-dimensional Euclidean space. The procedure thus appears to be the...
.
Significance testing
Q uses expert systems that automatically select appropriate significance tests based on the structure of the data (e.g., multiple responses, numeric versus categorical). It uses Taylor Series Linearization to adjust for weights on standard tables and all tables are automatically corrected for multiple comparisons (by default, using the False Discovery RateFalse discovery rate
False discovery rate control is a statistical method used in multiple hypothesis testing to correct for multiple comparisons. In a list of rejected hypotheses, FDR controls the expected proportion of incorrectly rejected null hypotheses...
).
Reviews of Q
- Murtaza Haider, "Q: A new software for analyzing survey data", eKonometrics: a commentary on consumer markets, February 12, 2011.
- Tim Macer, "Software Review: Q data analysis software", Quirk's Marketing Research Review, August 2010.
- Scott MacLean, "Letters to the Editor", Research News, February 2009, Australian Market & Social Research Society.
- Craig Wyman, "Craig Wyman reviews Q, the quantitative analysis software", Research News, December 2008, Australian Market & Social Research Society.
Release history
Q.1 - October 2007Q.2 - April 2008
Q.3 - February 2009
Q.4 - October 2010