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2.1 Reflecting on your mathematical history
Your course might not include any maths or technical content but, at some point during your course, it’s likely that you’ll come across information represented in charts, graphs and tables. You’ll be expected to know how to interpret this information. This unit will help you to develop the skills you need to do this. This unit can be used in conjunction with the ‘More working with charts, graphs and tables’ unit, which looks into more ways to present statistical information and shows y
Author(s): The Open University

2 Reflection on mathematics
Your course might not include any maths or technical content but, at some point during your course, it’s likely that you’ll come across information represented in charts, graphs and tables. You’ll be expected to know how to interpret this information. This unit will help you to develop the skills you need to do this. This unit can be used in conjunction with the ‘More working with charts, graphs and tables’ unit, which looks into more ways to present statistical information and shows y
Author(s): The Open University

Introduction
Your course might not include any maths or technical content but, at some point during your course, it’s likely that you’ll come across information represented in charts, graphs and tables. You’ll be expected to know how to interpret this information. This unit will help you to develop the skills you need to do this. This unit can be used in conjunction with the ‘More working with charts, graphs and tables’ unit, which looks into more ways to present statistical information and shows y
Author(s): The Open University

5.2 Summary
Your course might not include any maths or technical content but, at some point during your course, it’s likely that you’ll come across information represented in charts, graphs and tables. You’ll be expected to know how to interpret this information. This unit will help you to develop the skills you need to do this. This unit can be used in conjunction with the ‘More working with charts, graphs and tables’ unit, which looks into more ways to present statistical information and shows y
Author(s): The Open University

Biometrics
This text manual introduces statistical analysis and its underlying philosophy, enabling students to understand how to describe the confidence they have in their analysis. Statistical analysis is one of the most widely used, and abused, techniques in the biological sciences. Statistics are ostensibly used to allow an investigator to be objective. That is, the researcher uses statistical tests to determine whether or not his/her hypothesis is supported by the data collected. Unfortunately, the
Author(s): No creator set

Statistical Reasoning I
Statistical Reasoning in Public Health provides an introduction to selected important topics in biostatistical concepts and reasoning through lectures, exercises, and bulletin board discussions. It represents an introduction to the field and provides a survey of data and data types. Specific topics include tools for describing central tendency and variability in data; methods for performing inference on population means and proportions via sample data; statistical hypothesis testing and its appl
Author(s): No creator set

Peirce And Fisher on the Place of Probability in Abductive Inference
In his analysis of inference into three types, deduction, induction, and abduction, C. S. Peirce maintains that probability plays an essential role in the first two, but not in the third. For a deductive argument, probability tells us the frequency with which the conclusion will hold given the premises; for an inductive argument, probability tells us the frequency with which the argument will hold true. However, probability has no role to play in abduction because there is, in Peirce's view, no
Author(s): No creator set

Epidemiological Thinking For Non-Specialists, Fall 2007
Introduction to methods and problems in research and applications where quantitative data is analyzed to reconstruct possible pathways of development of behaviors and diseases. Special attention given to social inequalities, changes over the life course, heterogeneous pathways, and controversies with implications for policy and practice. Case studies and course projects are shaped to accommodate students with interests in fields related to health, gerontology, education, psychology, sociology, a
Author(s): No creator set

Introduction to Applied Statistics, Summer 2003
This course provides graduate students in the sciences with an intensive introduction to applied statistics. Topics include descriptive statistics, probability, non-parametric methods, estimation methods, hypothesis testing, correlation and linear regression, simulation, and robustness considerations. Calculations will be done using handheld calculators and the Minitab Statistical Computer Software.
Author(s): No creator set

Statistics - an intuitive introduction : standard deviation
A standard way of measuring statistical variability: standard deviation and the associated concepts of variance and degrees of freedom.
Author(s): Field Richard Dr;Horton J.,C. Dr

15.075 Applied Statistics (MIT)
This course is an introduction to applied statistics and data analysis. Topics include collecting and exploring data, basic inference, simple and multiple linear regression, analysis of variance, nonparametric methods, and statistical computing. It is not a course in mathematical statistics, but provides a balance between statistical theory and application. Prerequisites are calculus, probability, and linear algebra. We would like to acknowledge the contributions that Prof. Roy Welsch (MIT), Pro
Author(s): Newton, Elizabeth

2.57 Nano-to-Macro Transport Processes (MIT)
This course provides parallel treatments of photons, electrons, phonons, and molecules as energy carriers, aiming at fundamental understanding and descriptive tools for energy and heat transport processes from nanoscale continuously to macroscale. Topics include the energy levels, the statistical behavior and internal energy, energy transport in the forms of waves and particles, scattering and heat generation processes, Boltzmann equation and derivation of classical laws, deviation from classica
Author(s): Chen, Gang

17.874 Quantitative Research Methods: Multivariate (MIT)
This course is the second semester in the statistics sequence for political science and public policy offered in the Political Science Department at MIT. The intellectual thrust of the course is a presentation of statistical models for estimating causal effects of variables. The model of an effect is a conditional mean (though we might imagine other effect). The notion of causality is the effect of one variable on another holding all else constant.
Author(s): Ansolabehere, Stephen

6.041 Probabilistic Systems Analysis and Applied Probability (MIT)
This course is offered both to undergraduates (6.041) and graduates (6.431), but the assignments differ. 6.041/6.431 introduces students to the modeling, quantification, and analysis of uncertainty. Topics covered include: formulation and solution in sample space, random variables, transform techniques, simple random processes and their probability distributions, Markov processes, limit theorems, and elements of statistical inference.

20.109 Laboratory Fundamentals in Biological Engineering (MIT)
This course introduces experimental biochemical and molecular techniques from a quantitative engineering perspective. Rigorous quantitative data collection, statistical analysis, and conceptual understanding of instrumentation design and application form the underpinnings of this course. The four discovery based modules include DNA Engineering, Protein Engineering, Systems Engineering, and Biomaterials Engineering. Additional information is available on the course Wiki (hosted on OpenWetWare.) T
Author(s): Engelward, Bevin,Endy, Drew,Kuldell, Natalie,Lerne

For many towns and cities, an individual book of street maps called an A to Z has been produced. You can look up the name of a street in the index, and it will give you the page number of the map that contains the street, plus the grid reference square for the street. There are different conventions for these grid references. You may have met several of these.

8.044 Statistical Physics I (MIT)
This course offers an introduction to probability, statistical mechanics, and thermodynamics. Numerous examples are used to illustrate a wide variety of physical phenomena such as magnetism, polyatomic gases, thermal radiation, electrons in solids, and noise in electronic devices.
Author(s): Lee, Young

5.72 Statistical Mechanics (MIT)
This course discusses the principles and methods of statistical mechanics. Topics covered include classical and quantum statistics, grand ensembles, fluctuations, molecular distribution functions, other concepts in equilibrium statistical mechanics, and topics in thermodynamics and statistical mechanics of irreversible processes.
Author(s): Cao, Jianshu

Biodiversity Consortium : Measuring Ecological Diversity 3 : Measuring Abundance and Diversity
This package looks at how you measure ecological diversity at the regional level, and tackles more general questions relatinv to the various diversity indices and abundance models available. This package looks at species richness, relative abundance plots, diversity indices as well as covering such issues as sampling effort and the practical implications of using these statistical tests in applied ecology.
Author(s): Biodiversity Consortium / David Raffaelli and John

Biodiversity Consortium_KrugerWorld_ORP_1_raw_data
Raw data for a mammalian census of Kruger National Park, separated into habitat. Data can be uploaded to excel for statistical analysis. Also contains background information on biodiversity indices and models. Web pages which should run on any pc / mac / VLE with javascript enabled
Author(s): Biodiversity Consortium