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Math, Statistics, & Research Methods: Statistical Methods Websites

  • Algebra Calculator Algebra Calculator is a calculator that gives step-by-step help on algebra problems.
  • GeoGebra offers a free online apps bundle wtih graphing, geometry, algebra, 3D, statistics, probability.
  • Good Calculators Good Calculators offers a collection of free online calculators for personal and business use. These calculators have been programmed to work on smart phones, tablets, and computers.
  • Math Portal Provides lessons on learning algebra, calculus, analytic geometry, and linear algebra; more than 500 formulas, online calculators; and 46 tests with 503 questions in 16 categories.
  • provides a complete online College Algebra course. Unlike a traditional math classroom, we offer the one-on-one learning experience that every student needs to conquer College Algebra.
  • MathWorld Eric Weisstein's World of Mathematics (MathWorldTM) is an interactive mathematics encyclopedia intended for students, educators, math enthusiasts, and researchers.
  • Sloane's On-line Encyclopedia of Integer Sequences Online database of over 220,000 sequences. Each entry contains the leading terms of the sequence, keywords, mathematical motivations, literature links, and more, including the option to generate a graph or play a musical representation of the sequence.
  • The Math Forum The leading online resource for improving math learning, teaching, and communication since 1992, offering a wealth of problems and puzzles, online mentoring, research, team problem solving, collaborations, and professional development.
  • Wolfram Alpha Wolfram Alpha is a set of data and algorithms used for answering questions in a variety of subject domains. The aim of this product is to enable users to quickly engage in data computation and information visualization.

SPSS Tutorials

Although it is named "SPSS Tutorials," there is a great deal of information about how statistical tests work that goes beyond SPSS. Created by Kent State University Statistical Consultations.
Section 1: Intro to the SPSS Environment:

  • Navigate the SPSS interface using the drop-down menus or syntax.
  • Create a new dataset or import data from a file.

Section 2: Working with Data covers data manipulation and cleaning of all kinds.

  • Create, modify, or compute new variables.
  • Manipulate a dataset by splitting, merging, or transposing techniques.

Section 3: Exploring the Data.

  • Generate descriptive statistics for numeric variables.
  • Create frequency tables and crosstabulations of categorical variables.
  • Graph the distributions or relationships of variables.
  • Interpret these measures.

Section 4: Analyzing the Data. This section incorporates hypothesis testing.

  • Associations (Chi-Square, Pearson's Correlation).
  • Comparing means (One Sample t Test, Independent Samples t Test, Paired Samples t Test, One-Way ANOVA).
  • Predictive models (Multiple Regression, Logistic Regression, Ordinal Regression).


Data is the raw ingredient(s) from which statistics are created. Statistics are useful when you just need a few numbers to support an argument (ex. In 2003, 98.2% of American households had a television set--from Statistical Abstract of the United States). Statistics are usually presented in tables. Statistical analysis can be performed on data to show relationships among the variables collected. Through secondary data analysis, many different researchers can re-use the same data set for different purposes.

Aggregate/Macro Data vs. Microdata

Aggregate or Macro Data are higher-level data that have been compiled from smaller units of data. For example, the Census data that you find on Explore Census Data have been aggregated to preserve the confidentiality of individual respondents. Microdata contain individual cases, usually individual people, or in the case of Census data, individual households. The Integrated Public Use Microdata Sample (IPUMS) for the Census provides access to the actual survey data from the Census, but eliminates information that would identify individuals.

Data Sets, Studies, and Series

In data archives, a data set or study is made up of the raw data file and any related files, usually the codebook and setup files. The codebook is your guide to making sense of the raw data. For survey data, the codebook usually contains the actual questionnaire and the values for the responses to each question. The setup files help will not display properly.

Types of Data

Cross-Sectional describes data that are only collected once.

Time Series study the same variable over time. The National Health Interview Survey is an example of time series data because the questions generally remain the same over time, but the individual respondents vary.

Longitudinal Studies describe surveys that are conducted repeatedly, in which the same group of respondents are surveyed each time. This allows for examining changes over the life course. The Project on Human Development in Chicago Neighborhoods (PHDCN) Series contains a longitudinal component that tracks changes in the lives of individuals over time through interviews.

(Originally from Sue Erickson at Vanderbilt University)

  • Getting Started with SPSS for Windows
  • Tutorial by Indiana University that cover the SPSS interface, data preparation, and SPSS output. The tutorial also covers descriptive statistics and OLS.
  • SPSS Official Manuals
    The official manuals for version are free to the public online from SPSS website.
  • SPSS Syntax
    Many users choose SPSS for its user-friendly interface, however, don't satisfy yourself with it. The Syntax will provide great productivity, and this website will offer effectiveness in learning SPSS Syntax.
  • SPSS Tutorial
    The tutorial is prepared by Academic Technology Services in UCLA. It has a Starter Kit for beginners, and also topics for a range of data analysis models.

R is a language and environment for statistical computing and graphics which provides a wide variety of statistical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, etc. The program uses graphical techniques, and is highly extensible. R is similar to the S language and environment developed at Bell Laboratories (now Lucent Technologies), and most S code also runs in R.

R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of platforms, including Window,s MacOS, UNIX, FreeBSD, and Linux.