Controlling for test variables

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alguns apontamentos sobre testes com vars de controlo

3.2  Three (or more) variables

[Page last updated 3 August 2016]

Introducing a third variable. Controlling for test variables. Elaboration.

Logical model is X Y . T (the effect of X on Y controlling for T) where:

Y = Dependent variable
X = Independent variable
T = Test variable(s)

3.2.1 Elaboration

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What is SPSS?

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Uma explicação para as ciências sociais

What is SPSS and what does it do?

SPSS consists of an integrated series of computer programs which enable the user to read data from questionnaire surveys and other sources (e.g. medical and administrative records) to manipulate them in various ways and to produce a wide range of statistical analyses and reports, together with documentation.

Most users will have access to SPSS via their college or workplace or by purchasing the Gradpack version (specially priced for students).  Full  details are on IBM SPSS Solutions for  Education and there is a comparison table showing what is available in each version.

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Summary guide to SPSS tutorials

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Bom site com vários recursos sobre a utilização do IBM SPSS

Catalogue of SPSS tutorials is an Excel *.xlms file containing a full listing (with hyperlinks) of all tutorial files.[may not be completely up-to-date]

Guide to pop-out menus shows all the screenshots for menus and sub-menus for Survey  Analysis Workshop [may not be completely up-to-date and site has been re-organised, so needs a re-write, but still useful to show you what to expect]

There are more than 600 pages of downloadable tutorials arranged in four blocks.

Block  1: From questionnaire to SPSS saved file

1.1:   The language of survey analysis
1.2:   How do data relate to questionnaires?
1.3:   Reading raw data into SPSS
1.4:   Completing your data dictionary
1.5:   Utilities [still in preparation]

Block 2:  Analysing one variable

2.1:   Nominal and ordinal variables
2.2:   Interval scale variables
2.3:   Data transformations

Block 3:  Analysing two variables (and sometimes three)

3.1   Contingency tables
3.2   Three variables
3.3    Multiple response
3.4    Comparing means
3.5:   Conditional transformations

Block 4:   Hypothesis testing
[Still in preparation: provisional contents listed below: page also has links to some useful resources for statistical concepts]

Hypothesis testing
4.2a  t-test and one way anova
4.2b  Testing differences between three or more means
4.3  Chi-square (has one tutorial)
4.4  Regression and correlation
4.5  Association, structure and cause

SPSS files and documentation used for tutorials and exercises

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SPSS videos e trials

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Um site da IBM com bastantes recursos sobre o SPSS

Software Trial: IBM SPSS Statistics Desktop

Start leveraging your data today to identify your best customers, forecast future trends, improve supplier performance, and more.

Try trial

Software Trial: IBM SPSS Text Analytics for Surveys Trial Software [US]

Software Trial: IBM SPSS Text Analytics for Surveys Trial Software [US]

IBM SPSS Text Analytics for Surveys uses powerful natural language processing technologies specifically designed for survey text.

Try trial

Software Trial: IBM SPSS Amos Trial

Software Trial: IBM SPSS Amos Trial

IBM SPSS Amos gives you the power to easily perform structural equation modeling (SEM).

Try trial

Online Demo: IBM SPSS Regression in action

Online Demo: IBM SPSS Regression in action

Watch how powerful regression techniques can help you discover hidden relationships in your data.

Download

Online Demo: Two-step cluster analysis: Find natural groups in your data [US]

Online Demo: Two-step cluster analysis: Find natural groups in your data [US]

Watch a short demonstration of the two-step cluster analysis technique in SPSS Statistics Base.

Download

Online Demo: Online Demo: Statistical analysis with confidence using IBM SPSS Statistics [US]

Online Demo: Online Demo: Statistical analysis with confidence using IBM SPSS Statistics [US]

Explore the power of statistical analysis in your organization IBM Analytics IBM Analytics

Download

White Paper: White Paper: Better decision making under uncertain conditions [US]

White Paper: White Paper: Better decision making under uncertain conditions [US]

This paper describes Monte Carlo simulation, the value of this technique for risk analysis and how SPSS Statistics and its Monte Carlo simulation capabilities can help businesses assess for risk.

Read paper

White Paper: The Risk of Using Spreadsheets for Statistical Analysis [US]

White Paper: The Risk of Using Spreadsheets for Statistical Analysis [US]

Despite their popularity, spreadsheets may not be well suited for analysis and decision making. This paper explores why, and describes a better alternative.

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Raynald’s SPSS Tools

Reynald SPSS

Bons recursos sobre SPSS e ligação com R e Pyton

Raynald’s SPSS Tools

The collection of syntaxes, macros, scripts and hints for better solutions of data management and data analysis problems in IBM SPSS Statistics

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Random Probability, Mathematical Statistics, Stochastic Processes

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Um site organizado por temas como um livro com apps interessantes

Welcome!

Random (formerly Virtual Laboratories in Probability and Statistics) is a website devoted to probability, mathematical statistics, and stochastic processes, and is intended for teachers and students of these subjects. The site consists of an integrated set of components that includes expository text, interactive web apps, data sets, biographical sketches, and an object library. Please read the Introduction for more information about the content, structure, mathematical prerequisites, technologies, and organization of the project. Random is hosted at two sites: www.math.uah.edu/stat/ and www.randomservices.org/stat/. For updates, please follow @randomservices on Twitter.

Basic Information

Expository Chapters

  1. Foundations
  2. Probability Spaces
  3. Distributions
  4. Expected Value
  5. Special Distributions
  6. Random Samples
  7. Point Estimation
  8. Set Estimation
  9. Hypothesis Testing
  10. Geometric Models
  11. Bernoulli Trials
  12. Finite Sampling Models
  13. Games of Chance
  14. The Poisson Process
  15. Renewal Processes
  16. Stochastic Processes
  17. Markov Chains
  18. Brownian Motion

Ancillary Materials

Support and Navigation

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Rice Virtual Lab in Statistics Demos

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Pequenas apps em java para demonstrar diferentes temas em estatística

Mean and Median

Sampling Distribution Simulation

Confidence Intervals

Normal Approximation to the Binomial Distribution

Confidence Interval on a Proportion

Components of r

Regression by Eye

Restriction of Range

Repeated Measures

A “Small” Effect Size Can Make a Large Difference

Chi Square Test of Deviations from Expected Frequencies

2 x 2 Contingency Tables

Reliability and Regression Analysis

Histograms, Bin Widths, and Cross Validation

Transformations

Regression to the mean

Comparing distributions

Unequal n ANOVA and Types of Sums of Squares

Robustness of t test and ANOVA

One-way ANOVA

Two-way ANOVA

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KNIME Community Contributions

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Boa fonte de novos nós do KNIME, evitando q estejamos a programar algo q já foi programado antes.

KNIME Community Contributions offer a wide range of KNIME nodes from different application areas, such as chemo- and bioinformatics, image processing, or information retrieval. In contrast to the extensions available via the standard KNIME Update Site they are provided and maintained by various community developers.

The Trusted Community Contributions can easily be installed by selecting File -> Install KNIME Extensions in KNIME. Additional extensions are available by enabling the Update Site in KNIME via File -> Preferences -> Install/Update -> Available Update Sites. See the update site guide for details.

You can also download the whole update site as a ZIP archive and add the ZIP to the Available Update Sites (see above).

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The Statistics Portal

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Um portal cheio de facts & figures
One of the world’s largest statistics portals

We pride ourselves in being one of the world’s first and only companies to bring together data from over 18,000 sources.
Our research analysts source the most up-to-date statistical data from around the globe; our analytical approach and efficient research processes enable us to supply our clients with the data that is relevant to them.

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Comprehensive Guide to Data Visualization in R

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Bom resumo de alguns tipos de gráficos que podem ser obtidos no R, do mais simples a alguns mais complexos.

This visualization (originally created using Tableau) is a great example of how data visualization can help decision makers. Imagine telling this information to an investor through a table. How long do you think you will take to explain it to him?

With ever increasing volume of data in today’s world, it is impossible to tell stories without these visualizations. While there are dedicated tools like Tableau, QlikView and d3.js, nothing can replace a modeling / statistics tools with good visualization capability. It helps tremendously in doing any exploratory data analysis as well as feature engineering. This is where R offers incredible help.

R Programming offers a satisfactory set of inbuilt function and libraries (such as ggplot2, leaflet, lattice) to build visualizations and present data. In this article, I have covered the steps to create the common as well as advanced visualizations in R Programming.

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