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Introduction to Statistical Packages Eugene Tseytlin Deparment of BioMedical Informatics University of Pittsburgh.

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Presentation on theme: "Introduction to Statistical Packages Eugene Tseytlin Deparment of BioMedical Informatics University of Pittsburgh."— Presentation transcript:

1 Introduction to Statistical Packages Eugene Tseytlin Deparment of BioMedical Informatics University of Pittsburgh

2 Expectations NOT to become an expert in any statistical software package NOT to become an expert statistician Present an Overview of what solutions are available with emphasis on free open source software

3 About Me Who Senior Software Developer Where Department of BioMedical Informatics, University of Pittsburgh Areas of Expertise Intelligent Tutoring Systems (ITS) Natural Language Processing (NLP) Digital Imaging: digital microscopy and fMRI Machine Learning Technologies Java, Matlab, R, RapidMiner, SAS, C/C++, OWL, PHP, Perl

4 Introduction Overview of what is available for statistical analysis Overview of what is popular today and what are the trends for tomorrow Overview of some individual software packages Overview of the dataset that we will be using in next lecture

5 Available Statistical Packages Proprietary Excel SPSS MINITAB SAS Free Software LibreOffice Calc PSPP EpiInfo R

6 What is Used? (Academia) Figure 7a. Use of data analysis software in academic publications as measured by hits on Google Scholar.

7 What is Used? (Survey)

8 What is Used? (Job Market)

9 Microsoft Excel

10 COST Individual License for Microsoft Office Professional $350 Microsoft Office University Student License: $99 Volume Discounts available for large organizations and universities Free Starter Version available on some new PCs PRO Nearly ubiquitous and is often pre-installed on new computers User friendly Very good for basic descriptive statistics, charts and plots CON Costs money Not sufficient for anything beyound the most basic statistical analysis

11 Minitab

12 COST $1,395.00 per single user license PRO Easy to learn and use Often taught in schools in introductory statistics courses Widely used in engineering for process improvement CON Costs Money Not suitable for very complicated statistical computation and analysis Not often used in academic research

13 SPSS

14 COST From $1000 to $12000 per license depending on license type. CON Very expensive Not adequate for modeling and cutting edge statistical analysis PRO Easy to learn and use More powerful then Minitab One of the most widely used statistical packages in academia and industry Has a command line interface in addition to menu driven user intefrace One of the most powerful statistical package that is also easy to use.

15 SAS

16 COST Complicated pricing model $8,500 first year license fee CON Very very expensive Not user friendly Steap learning curve Relatively poor graphics capabilities PRO Widely accepted as the leader in statistical analysis and modeling Widely used in the industry and academia Very flexible and very powerful.

17 LibreOffice Calc

18 LibreOffice is a free and open source office suite, developed by The Document Foundation. It is descended from OpenOffice.org, from which it was forked in 2010 OpenOffice vs LibreOffice Star → Sun → Oracle → Apache, Document Foundation OpenOffice http://www.openoffice.org/download http://www.openoffice.org/download LibreOffice http://www.libreoffice.org/download/ http://www.libreoffice.org/download/

19 LibreOffice Calc PRO Very similar to Microsoft Excel in functionality and look and feel (earlier versions) User friendly Very good for basic descriptive statistics, charts and plots Inter-operable with Microsoft Office COST Free CON Not sufficient for anything beyound the most basic statistical analysis

20 EpiInfo

21 Epi Info is public domain statistical software for epidemiology developed by Centers for Disease Control and Prevention (CDC) Epi Info has been in existence for over 20 years and is currently available for Microsoft Windows. The program allows for electronic survey creation, data entry, and analysis. Within the analysis module, analytic routines include t-tests, ANOVA, nonparametric statistics, cross tabulations and stratification with estimates of odds ratios, risk ratios, and risk differences, logistic regression (conditional and unconditional), survival analysis (Kaplan Meier and Cox proportional hazard), and analysis of complex survey data. The software is in the public domain, free, and can be downloaded from http://www.cdc.gov/epiinfo. Limited support is available

22 EpiInfo PRO Consists of multiple modules to accomplish various tasks beyond just statistical analysis. ability to rapidly develop a questionnaire customize the data entry process quickly enter data into that questionnaire analyze the data COST Free CON Not a dedicated statistical package Not as powerful as commercial alternative for performing advanced analysis and modeling

23 PSPP

24 COST Free PRO Aims as a free SPSS alternative with an interface that closely resembles SPSS User friendly Good enough for basic statistical analysis CON Lacks many advanced statistical tests and features that are present in SPSS Last version released in 2010 Not very well known nor widely used

25 R

26 R R provides a wide variety of statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and others. R is easily extensible through functions and extensions, and the R community is noted for its active contributions in terms of packages. There are some important differences, but much code written for S runs unaltered. Many of R's standard functions are written in R itself, which makes it easy for users to follow the algorithmic choices made. R is highly extensible through the use of user-submitted packages for specific functions or specific areas of study. Due to its S heritage, R has stronger object-oriented programming facilities than most statistical computing languages. Extending R is also eased by its permissive lexical scoping rules.[10] According to Rexer's Annual Data Miner Survey in 2010, R has become the data mining tool used by more data miners (43%) than any other.[11] Another strength of R is static graphics, which can produce publication-quality graphs, including mathematical symbols. Dynamic and interactive graphics are available through additional packages.[12]

27 R PRO Widely used and accepted in industry and academia Very powerful and flexible Very large user base Lots of books and manuals Several User Interface Shells available COST Free / Open Source CON Not user friendly Requires steep learning curve

28 Dataset The Dataset and Story Library http://lib.stat.cmu.edu/DASL/ DASL (pronounced "dazzle") is an online library of datafiles and stories that illustrate the use of basic statistics methods. We hope to provide data from a wide variety of topics so that statistics teachers can find real-world examples that will be interesting to their students. Use DASL's powerful search engine to locate the story or datafile of interest.

29 Brain Size and Intelligence Are the size and weight of your brain indicators of your mental capacity? In this study by Willerman et al. (1991) the researchers use Magnetic Resonance Imaging (MRI) to determine the brain size of the subjects. The researchers take into account gender and body size to draw conclusions about the connection between brain size and intelligence. http://lib.stat.cmu.edu/DASL/Stories/BrainSizeandIntelligence.html Methods Correlation Regression Scatterplot

30 Brain Size and Intelligence Description: Willerman et al. (1991) collected a sample of 40 right-handed Anglo introductory psychology students at a large southwestern university. Subjects took four subtests (Vocabulary, Similarities, Block Design, and Picture Completion) of the Wechsler (1981) Adult Intelligence Scale-Revised. The researchers used Magnetic Resonance Imaging (MRI) to determine the brain size of the subjects. Information about gender and body size (height and weight) are also included. The researchers withheld the weights of two subjects and the height of one subject for reasons of confidentiality. Number of cases: 40 Variable Names: Gender: Male or Female FSIQ: Full Scale IQ scores based on the four Wechsler (1981) subtests VIQ: Verbal IQ scores based on the four Wechsler (1981) subtests PIQ: Performance IQ scores based on the four Wechsler (1981) subtests Weight: body weight in pounds Height: height in inches MRI_Count: total pixel Count from the 18 MRI scans

31 Conclusion Statistical analysis is an integral part of any study and publication While commercial statistical software may cost an arm and a leg, free alternatives do exists. While some free alternatives don't measure up, others are growing and expending rapidly and may overtake commercial software in features and popularity

32 References https://sites.google.com/site/r4statistics/popularity http://en.freestatistics.info/ http://lib.stat.cmu.edu/ http://www.comfsm.fm/~dleeling/statistics/notes000.html


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