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Host a 'Statistics Icebreaker' where students introduce themselves by stating their name and one interesting statistical fact about their lives. This could include anything from the number of countries they've visited to the number of pets they own. It's a fun way to get students comfortable with the idea of statistics.

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Organize a simple probability game using dice. Have students predict the outcome of rolling two dice and calculate the probabilities of different sums to introduce basic probability concepts that are foundational in statistics.

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Understanding the Relevance of Statistics

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Understanding the Relevance of Statistics

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Show a compelling video that highlights the importance and application of statistics in various fields like healthcare, business, and science. This can help students appreciate the real-world relevance of what they're about to learn.

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Assign small groups to collect data from their surroundings on a topic of their choice and present their findings. This activity involves data collection, analysis, and interpretation, helping students grasp these critical steps in statistical studies.

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Present a brief history of statistics and introduce students to key figures in the field such as Florence Nightingale and Ronald Fisher. Discuss their contributions to help students understand the evolution of statistical methods.

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Ask students to bring in a news article that includes some form of data or statistics. In class, discuss the representation and interpretation of this data, promoting critical thinking about how statistics are used in media.

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Precise and Rapid Clinical Genomics Data Interpretation

A new approach to precision medicine efficiently and accurately associates disease biomarkers with clinical evidence.

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Data Interpretation News, Articles | The Scientist Magazine®

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The Scientist's articles tagged with: data interpretation

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Encourage students to create infographics using the data collected in earlier assignments or based on their research. This develops their ability to visually represent data and statistics in a compelling and understandable way.

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Provide a beginner tutorial session on how to use statistical software such as SPSS or R. This introduces students to tools they will use throughout their statistical studies.

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gretl is an example of an open-source statistical package

ADaMSoft - a generalized statistical software with data mining algorithms and methods for data management

Chronux - for neurobiological time series data

DAP - free replacement for SAS

Environment for DeveLoping KDD-Applications Supported by Index-Structures (ELKI) a software framework for developing data mining algorithms in Java

Epi Info - statistical software for epidemiology developed by Centers for Disease Control and Prevention (CDC). Apache 2 licensed[1]

Fityk - nonlinear regression software (GUI and command line)

GNU Octave - programming language very similar to MATLAB with statistical features

gretl - gnu regression, econometrics and time-series library

intrinsic Noise Analyzer (iNA) - For analyzing intrinsic fluctuations in biochemical systems

jamovi - A free software alternative to IBM SPSS Statistics

JASP - A free software alternative to IBM SPSS Statistics with additional option for Bayesian methods

Just another Gibbs sampler (JAGS) - a program for analyzing Bayesian hierarchical models using Markov chain Monte Carlo developed by Martyn Plummer. It is similar to WinBUGS

LIBSVM - C++ support vector machine libraries

mlpack - open-source library for machine learning, exploits C++ language features to provide maximum performance and flexibility while providing a simple and consistent application programming interface (API)

Mondrian - data analysis tool using interactive statistical graphics with a link to R

Neurophysiological Biomarker Toolbox - Matlab toolbox for data-mining of neurophysiological biomarkers

OpenBUGS

OpenEpi - A web-based, open-source, operating-independent series of programs for use in epidemiology and statistics based on JavaScript and HTML

OpenNN - A software library written in the programming language C++ which implements neural networks, a main area of deep learning research

Orange, a data mining, machine learning, and bioinformatics software

Pandas - High-performance computing (HPC) data structures and data analysis tools for Python in Python and Cython (statsmodels, scikit-learn)

Perl Data Language - Scientific computing with Perl

Ploticus - software for generating a variety of graphs from raw data

PSPP - A free software alternative to IBM SPSS Statistics

R - free implementation of the S (programming language)

ROOT - an open-source C++ system for data storage, processing and analysis, developed by CERN and used to find the Higgs boson

Salstat - menu-driven statistics software

Scilab - uses GPL-compatible CeCILL license

SciPy - Python library for scientific computing that contains the stats sub-package which is partly based on the venerable |STAT (a.k.a. PipeStat, formerly UNIX|STAT) software

scikit-learn - extends SciPy with a host of machine learning models (classification, clustering, regression, etc.)

statsmodels - extends SciPy with statistical models and tests (regression, plotting, example datasets, generalized linear model (GLM), time series analysis, autoregressive-moving-average model (ARMA), vector autoregression (VAR), non-parametric statistics, ANOVA, empirical likelihood)

Shogun (toolbox) - open-source, large-scale machine learning toolbox that provides several SVM (Support Vector Machine) implementations (like libSVM, SVMlight) under a common framework and interfaces to Octave, MATLAB, Python, R

Simfit - simulation, curve fitting, statistics, and plotting

SOCR

SOFA Statistics - desktop GUI program focused on ease of use, learn as you go, and beautiful output

Stan (software) - open-source package for obtaining Bayesian inference using the No-U-Turn sampler, a variant of Hamiltonian Monte Carlo. It is somewhat like BUGS, but with a different language for expressing models and a different sampler for sampling from their posteriors

Statistical Lab - R-based and focusing on educational purposes

Weka (machine learning) - a suite of machine learning software written at the University of Waikato

CSPro (core is public domain but without publicly available source code; the web UI has been open sourced under Apache version 2[2] and the help system under GPL version 3[3])

Dataplot (NIST)

X-13ARIMA-SEATS (public domain in the United States only; outside of the United States is under US government copyright)[4]

Alteryx - analytics platform with drag and drop statistical models; R and Python integration

Analytica - visual analytics and statistics package

Angoss - products KnowledgeSEEKER and KnowledgeSTUDIO incorporate several data mining algorithms

ASReml - for restricted maximum likelihood analyses

BMDP - general statistics package

DataGraph - visual analysis with linear and nonlinear regression

DB Lytix - 800+ in-database models

EViews - for econometric analysis

FAME (database) - a system for managing time-series databases

GAUSS - programming language for statistics

Genedata - software for integration and interpretation of experimental data in the life science R&D

GenStat - general statistics package

GLIM - early package for fitting generalized linear models

GraphPad InStat - very simple with much guidance and explanations

GraphPad Prism - biostatistics and nonlinear regression with clear explanations

Igor Pro - programming language with statistical features and numerical analysis

IMSL Numerical Libraries - software library with statistical algorithms

JMP - visual analysis and statistics package

LIMDEP - comprehensive statistics and econometrics package

LISREL - statistics package used in structural equation modeling

Maple - programming language with statistical features

Mathematica - a software package with statistical particularly ŋ features

MATLAB - programming language with statistical features

MedCalc - for biomedical sciences

Microfit - econometrics package, time series

Minitab - general statistics package

MLwiN - multilevel models (free to UK academics)

Nacsport Video Analysis Software - software for analysing sports and obtaining statistical intelligence

NAG Numerical Library - comprehensive math and statistics library

NCSS - general statistics package

Neural Designer - commercial deep learning package

NLOGIT - comprehensive statistics and econometrics package

nQuery Sample Size Software - Sample Size and Power Analysis Software[5]

O-Matrix - programming language

OriginPro - statistics and graphing, programming access to NAG library

PASS Sample Size Software (PASS) - power and sample size software from NCSS

Plotly - plotting library and styling interface for analyzing data and creating browser-based graphs. Available for R, Python, MATLAB, Julia, and Perl

Primer-E Primer - environmental and ecological specific

PV-WAVE - programming language comprehensive data analysis and visualization with IMSL statistical package

Qlucore Omics Explorer - interactive and visual data analysis software

RapidMiner - machine learning toolbox

Regression Analysis of Time Series (RATS) - comprehensive econometric analysis package

Rguroo Statistical Software - An online statistical software designed for teaching and analyzing data

S-PLUS - general statistics package

SAS (software) - comprehensive statistical package

SHAZAM (Econometrics and Statistics Software) - comprehensive econometrics and statistics package

SigmaStat - package for group analysis

Simul - econometric tool for multidimensional (multi-sectoral, multi-regional) modeling

Speakeasy (computational environment) - numerical computational environment and programming language with many statistical and econometric analysis features

SPSS Modeler - comprehensive data mining and text analytics workbench

SPSS Statistics - comprehensive statistics package

Stata - comprehensive statistics package

StatCrunch - comprehensive statistics package, originally designed for college statistics courses

Statgraphics - general statistics package

Statistica - comprehensive statistics package

StatsDirect - statistics package designed for biomedical, public health and general health science uses

StatXact - package for exact nonparametric and parametric statistics

SuperCROSS - comprehensive statistics package with ad-hoc, cross tabulation analysis

Systat - general statistics package

The Unscrambler - free-to-try commercial multivariate analysis software for Windows

Unistat - general statistics package that can also work as Excel add-in

WarpPLS - statistics package used in structural equation modeling

Wolfram Language[6] - the computer language that evolved from the program Mathematica. It has similar statistical capabilities as Mathematica.

World Programming System (WPS) - statistical package that supports the use of Python, R and SAS languages within a single user program.

XploRe

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List of statistical software - Wikipedia

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Organize a class debate on a topic with statistical significance. Students will need to research and use statistical data to support their arguments, fostering a deeper understanding of how statistics inform opinions.

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Show the 'The Joy of Stats' documentary or snippets to spark students' interest in the beauty and fun of statistics. This can help students develop a more positive and engaged attitude towards the subject.

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Hans Rosling's 200 Countries, 200 Years, 4 Minutes - The Joy of Stats - BBC