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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MARS – Multivariate Adaptive Regression Splines

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Boa descrição destes algoritmos de análise de dados pelos proprios autores

An Overview of MARS

What is “MARS”?

MARS®, an acronym for Multivariate Adaptive Regression Splines, is a multivariate non-parametric regression procedure introduced in 1991 by world-renowned Stanford statistician and physicist, Jerome Friedman (Friedman, 1991). Salford Systems’ MARS, based on the original code, has been substantially enhanced with new features and capabilities in exclusive collaboration with Friedman.

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How to create a slicer in Excel

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Bom tutorial de como usar umas das novas funcionalidades do Excel

For dashboards and quick filtering, you can’t beat Excel slicers. They’re easy to implement and even easier to use. Here are the basics–plus a few power tips.

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Best Data Science Learning podcasts

KDnuggets

Muito bons podcasts tem temas introdutórios

We present the top 12 Data Science & Machine Learning related Podcasts by popularity on iTunes. Check out latest episodes to stay up-to-date & become a part of the data conversations!

By Bhavya Geethika Peddibhotla.

Learn Data science the new way by listening to these compelling story tellers, interviewers, educators and experts in the field. Data suggests that podcasting about Data Science is only growing!

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Straightforward Statistics Videos

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Montes de vídeos sobre todos os temas abordados em P&E

Video and Multimedia

Click on the following links. Please note these will open in a new window.

Descriptive Versus Inferential Statistics
https://www.youtube.com/watch?v=edEXEyvG4Wk
Illustrates the differential purposes served by descriptive and inferential techniques in conducting statistical analyses.

https://www.youtube.com/watch?v=L6hy1CY-OW4
Practical examples of descriptive and inferential statistics

https://www.youtube.com/watch?v=be9e-Q-jC-0
Simple Random Sampling, Convenience Sampling, Systematic Sampling, Cluster Sampling, Stratified Sampling

Types of Variables
https://www.youtube.com/watch?v=hZxnzfnt5v8
Describes the concepts of; a) unit of observation and b) variables and consequently the differences amongst the three major levels of measurement of variables, nominal, ordinal and interval/ratio.

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INTRODUCTORY STATISTICS book

http://www.psychstat.missouristate.edu/IntroBook3/sbk.htm

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Um webBook sobre estatística com exercícios e exemplos em SPSS

INTRODUCTORY STATISTICS:
CONCEPTS, MODELS, AND APPLICATIONS

3rd Web Edition

David W. Stockburger

Missouri State University

@Copyright 2013 by David W. Stockburger

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Earliest Known Uses of Words of Mathematics

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um curioso site onde se registam os significados mais antigos para termos matemáticos

These pages attempt to show the first uses of various words used in mathematics. Research for these pages is ongoing, and a citation should not be assumed to be the earliest use unless it is indicated as such.

Mathematical Words: Origins and Sources by John Aldrich is an excellent article and companion to this web site.

Please see also Earliest Uses of Various Mathematical Symbols, Images of Mathematicians on Postage Stamps, and Ambiguously Defined Mathematical Terms at the High School Level.

These pages are maintained by Jeff Miller, a teacher at Gulf High School in New Port Richey, Florida. The principal contributors are John Aldrich, Julio González Cabillón, Carlos César de Araújo, and James A. Landau. Other contributors are Manoel de Campos Almeida, Antranig Basman, Dave Cohen, John Conway, Martin Davis, Karen Dee Michalowicz, Joanne M. Despres of Merriam-Webster Inc., Bill Dubuque, Mark Dunn, John G. Fauvel, Walter Felscher, Giovanni Ferraro, Tom Foregger, Michael N. Fried, John Harper, Antreas P. Hatzipolakis, Barnabas Hughes, Samuel S. Kutler, Franz Lemmermeyer, Avinoam Mann, Peter M. Neumann, Ken Pledger, Paul Pollack, Jim Propp, Aldo I. Ramirez, Lee Rudolph, Randy K. Schwartz, Max Urchs, Tom Walsh, William C. Waterhouse, and David Wilkins.

“Perhaps I may without immodesty lay claim to the appellation of Mathematical Adam, as I believe that I have given more names (passed into general circulation) of the creatures of mathematical reason than all the other mathematicians of the age combined.” —James Joseph Sylvester, Nature 37 (1888), p. 152.

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Research Methods Knowledge Base

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Um webBook pensado para investigadores sobre temas de estatística

What is the Research Methods Knowledge Base?

The Research Methods Knowledge Base is a comprehensive web-based textbook that addresses all of the topics in a typical introductory undergraduate or graduate course in social research methods.  It covers the entire research process including: formulating research questions; sampling (probability and nonprobability); measurement (surveys, scaling, qualitative, unobtrusive); research design (experimental and quasi-experimental); data analysis; and, writing the research paper.  It also addresses the major theoretical and philosophical underpinnings of research including: the idea of validity in research; reliability of measures; and ethics.  The Knowledge Base was designed to be different from the many typical commercially-available research methods texts.  It uses an informal, conversational style to engage both the newcomer and the more experienced student of research.  It is a fully hyperlinked text that can be integrated easily into an existing course structure or used as a sourcebook for the experienced researcher who simply wants to browse.

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A New View of Statistics

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Um webBook com montes de temas bem explicados

Mar 2013. Coming very soon: a slideshow and Excel workbook for an introductory course of 10 lectures on statistics. Aug 2011. Check out the following 2010 articles at Sportscience: assigning subjects to treatments in a controlled trial; regression vs limits of agreement in measure-comparison studies; magnitudes of effects derived from linear models. See the frame at right for links to much more, including the progressive statistics and research design articles. Previous updates…
New original approaches to statistics for researchers: the examples are taken from exercise and sport science, but the principles apply to all empirical sciences. Read more in the preface.
Feedback wanted: if you can’t understand something here, it’s my fault. Email me.
Become a license holder…eventually! Not yet. More…
Full Contents
Short Contents:
Preface: About These Pages
Summarizing Data
Simple Statistics & Effect Statistics
Dimension Reduction
Precision of Measurement
Generalizing to a Population
Confidence Limits & Statistical Significance
Statistical Models
Estimating Sample Size
Summary: The Most Important Points
Quiz
Reference: Hopkins, W. G. (2000). A new view of statistics. Internet Society for Sport Science: http://www.sportsci.org/resource/stats/.

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HyperStat Online Statistics Textbook

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Mais um eBook com montes de links para outros recursos

RVLS Home | Glossary | Free Statistical Analysis Tools | Instructional Demos | Exercises and Problems | Statistics Help | Privacy policy

Contents

  1. Introduction to Statistics
  2. Describing Univariate Data
  3. Describing Bivariate Data
  4. Introduction to Probability (elementary)
  5. Normal Distribution
  6. Sampling Distributions
  7. Point Estimation
  8. Confidence Intervals
  9. The Logic of Hypothesis Testing
  10. Testing Hypotheses with Standard Errors
  11. Power
  12. Introduction to Between-Subjects ANOVA
  13. Factorial Between-Subjects ANOVA
  14. Within-Subjects/Repeated Measures ANOVA
  15. Prediction
  16. Chi Square
  17. Distribution-Free Tests
  18. Measuring Effect Size

© 1993-2013 David M. Lane

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