Searching for statistics : 458 results found | RSS Feed for this search

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

5.62 Physical Chemistry II (MIT) 5.62 Physical Chemistry II (MIT)

Description

This subject deals primarily with elementary statistical mechanics, transport properties, kinetic theory, solid state, reaction rate theory, and chemical reaction dynamics.AcknowledgementsThe lecture note materials for this course include contributions from Professor Sylvia T. Ceyer. The Staff for this course would like to acknowledge that these course materials include contributions from past instructors, textbooks, and other members of the MIT Chemistry Department affiliated with course #5.62. Since the following works have evolved over a period of many years, no single source can be attributed. This subject deals primarily with elementary statistical mechanics, transport properties, kinetic theory, solid state, reaction rate theory, and chemical reaction dynamics.AcknowledgementsThe lecture note materials for this course include contributions from Professor Sylvia T. Ceyer. The Staff for this course would like to acknowledge that these course materials include contributions from past instructors, textbooks, and other members of the MIT Chemistry Department affiliated with course #5.62. Since the following works have evolved over a period of many years, no single source can be attributed.Subjects

physical chemistry | physical chemistry | partition functions | partition functions | atomic degrees of freedom | atomic degrees of freedom | molecular degrees of freedom | molecular degrees of freedom | chemical equilibrium | chemical equilibrium | thermodynamics | thermodynamics | intermolecular potentials | intermolecular potentials | equations of state | equations of state | solid state chemistry | solid state chemistry | einstein and debye solids | einstein and debye solids | kinetic theory | kinetic theory | rate theory | rate theory | chemical kinetics | chemical kinetics | transition state theory | transition state theory | RRKM theory | RRKM theory | collision theory | collision theory | equipartition | equipartition | fermi-dirac statistics | fermi-dirac statistics | boltzmann statistics | boltzmann statistics | bose-einstein statistics | bose-einstein statistics | statistical mechanics | statistical mechanicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata5.62 Physical Chemistry II (MIT) 5.62 Physical Chemistry II (MIT)

Description

This course covers elementary statistical mechanics, transport properties, kinetic theory, solid state, reaction rate theory, and chemical reaction dynamics. Acknowledgements The staff for this course would like to acknowledge that these course materials include contributions from past instructors, textbooks, and other members of the MIT Chemistry Department affiliated with course #5.62. Since the following works have evolved over a period of many years, no single source can be attributed. This course covers elementary statistical mechanics, transport properties, kinetic theory, solid state, reaction rate theory, and chemical reaction dynamics. Acknowledgements The staff for this course would like to acknowledge that these course materials include contributions from past instructors, textbooks, and other members of the MIT Chemistry Department affiliated with course #5.62. Since the following works have evolved over a period of many years, no single source can be attributed.Subjects

physical chemistry | physical chemistry | partition functions | partition functions | atomic degrees of freedom | atomic degrees of freedom | molecular degrees of freedom | molecular degrees of freedom | chemical equilibrium | chemical equilibrium | thermodynamics | thermodynamics | intermolecular potentials | intermolecular potentials | equations of state | equations of state | solid state chemistry | solid state chemistry | einstein and debye solids | einstein and debye solids | kinetic theory | kinetic theory | rate theory | rate theory | chemical kinetics | chemical kinetics | transition state theory | transition state theory | RRKM theory | RRKM theory | collision theory | collision theory | equipartition | equipartition | fermi-dirac statistics | fermi-dirac statistics | boltzmann statistics | boltzmann statistics | bose-einstein statistics | bose-einstein statistics | statistical mechanics | statistical mechanicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-5.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataStatistical Methods for Planners I (MIT) Statistical Methods for Planners I (MIT)

Description

This course develops logical, empirically based arguments using statistical techniques and analytic methods. Elementary statistics, probability, and other types of quantitative reasoning useful for description, estimation, comparison, and explanation are covered. Emphasis is on the use and limitations of analytical techniques in planning practice. This course develops logical, empirically based arguments using statistical techniques and analytic methods. Elementary statistics, probability, and other types of quantitative reasoning useful for description, estimation, comparison, and explanation are covered. Emphasis is on the use and limitations of analytical techniques in planning practice.Subjects

statistics | statistics | statistical methods | statistical methods | quantitative reasoning | quantitative reasoning | variability | variability | numeracy | numeracy | measurement | measurement | stata | stata | logic | logic | probability | probability | inferential statistics | inferential statistics | regression | regression | census | census | bivariate | bivariate | multivariate | multivariate | normal curve | normal curve | research design | research design | decision tree | decision tree | utility | utility | planning | planning | distribution | distribution | city planning | city planning | scatterplot | scatterplotLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-11.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata18.443 Statistics for Applications (MIT) 18.443 Statistics for Applications (MIT)

Description

This course is a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. Topics include: hypothesis testing and estimation, confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, correlation, decision theory, and Bayesian statistics. Note: Please see the syllabus for a description of the different versions of 18.443 taught at MIT. This course is a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. Topics include: hypothesis testing and estimation, confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, correlation, decision theory, and Bayesian statistics. Note: Please see the syllabus for a description of the different versions of 18.443 taught at MIT.Subjects

hypothesis testing | hypothesis testing | hypothesis estimation | hypothesis estimation | confidence intervals | confidence intervals | chi-square tests | chi-square tests | nonparametric statistics | nonparametric statistics | analysis of variance | analysis of variance | regression | regression | correlation | correlation | decision theory | decision theory | Bayesian statistics | Bayesian statisticsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata18.443 Statistics for Applications (MIT) 18.443 Statistics for Applications (MIT)

Description

This course provides a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. The course topics include hypothesis testing and estimation. It also includes confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, and correlation. This course provides a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. The course topics include hypothesis testing and estimation. It also includes confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, and correlation.Subjects

hypothesis testing and estimation; confidence intervals; chi-square tests; nonparametric statistics; analysis of variance; regression; correlation | hypothesis testing and estimation; confidence intervals; chi-square tests; nonparametric statistics; analysis of variance; regression; correlation | hypothesis testing and estimation | hypothesis testing and estimation | confidence intervals | confidence intervals | chi-square tests | chi-square tests | nonparametric statistics | nonparametric statistics | analysis of variance | analysis of variance | regression | regression | correlation | correlationLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata18.443 Statistics for Applications (MIT) 18.443 Statistics for Applications (MIT)

Description

This course is a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. Topics include: hypothesis testing and estimation, confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, correlation, decision theory, and Bayesian statistics. This course is a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. Topics include: hypothesis testing and estimation, confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, correlation, decision theory, and Bayesian statistics.Subjects

hypothesis testing | hypothesis testing | hypothesis estimation | hypothesis estimation | confidence intervals | confidence intervals | chi-square tests | chi-square tests | nonparametric statistics | nonparametric statistics | analysis of variance | analysis of variance | regression | regression | correlation | correlation | decision theory | decision theory | Bayesian statistics | Bayesian statisticsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata18.443 Statistics for Applications (MIT) 18.443 Statistics for Applications (MIT)

Description

This course is a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. Topics include: hypothesis testing and estimation, confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, correlation, decision theory, and Bayesian statistics. Note: Please see the syllabus for a description of the different versions of 18.443 taught at MIT. This course is a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. Topics include: hypothesis testing and estimation, confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, correlation, decision theory, and Bayesian statistics. Note: Please see the syllabus for a description of the different versions of 18.443 taught at MIT.Subjects

hypothesis testing | hypothesis testing | hypothesis estimation | hypothesis estimation | confidence intervals | confidence intervals | chi-square tests | chi-square tests | nonparametric statistics | nonparametric statistics | analysis of variance | analysis of variance | regression | regression | correlation | correlation | decision theory | decision theory | Bayesian statistics | Bayesian statisticsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataDescription

This course introduces statistical tools and techniques that are routinely used by modern statisticians for a wide variety of applications. This free course may be completed online at any time. See course site for detailed overview and learning outcomes. (Mathematics 251)Subjects

statistics | regression | correlation | experimental design | parametric statistics | non-parametric statistics | Computer science | I100License

Attribution 2.0 UK: England & Wales Attribution 2.0 UK: England & Wales http://creativecommons.org/licenses/by/2.0/uk/ http://creativecommons.org/licenses/by/2.0/uk/Site sourced from

http://dspace.jorum.ac.uk/oai/request?verb=ListRecords&metadataPrefix=oai_dcAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata5.62 Physical Chemistry II (MIT)

Description

This subject deals primarily with elementary statistical mechanics, transport properties, kinetic theory, solid state, reaction rate theory, and chemical reaction dynamics.AcknowledgementsThe lecture note materials for this course include contributions from Professor Sylvia T. Ceyer. The Staff for this course would like to acknowledge that these course materials include contributions from past instructors, textbooks, and other members of the MIT Chemistry Department affiliated with course #5.62. Since the following works have evolved over a period of many years, no single source can be attributed.Subjects

physical chemistry | partition functions | atomic degrees of freedom | molecular degrees of freedom | chemical equilibrium | thermodynamics | intermolecular potentials | equations of state | solid state chemistry | einstein and debye solids | kinetic theory | rate theory | chemical kinetics | transition state theory | RRKM theory | collision theory | equipartition | fermi-dirac statistics | boltzmann statistics | bose-einstein statistics | statistical mechanicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

https://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata5.62 Physical Chemistry II (MIT)

Description

This course covers elementary statistical mechanics, transport properties, kinetic theory, solid state, reaction rate theory, and chemical reaction dynamics. Acknowledgements The staff for this course would like to acknowledge that these course materials include contributions from past instructors, textbooks, and other members of the MIT Chemistry Department affiliated with course #5.62. Since the following works have evolved over a period of many years, no single source can be attributed.Subjects

physical chemistry | partition functions | atomic degrees of freedom | molecular degrees of freedom | chemical equilibrium | thermodynamics | intermolecular potentials | equations of state | solid state chemistry | einstein and debye solids | kinetic theory | rate theory | chemical kinetics | transition state theory | RRKM theory | collision theory | equipartition | fermi-dirac statistics | boltzmann statistics | bose-einstein statistics | statistical mechanicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

https://ocw.mit.edu/rss/all/mit-allcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataNumbers are Weapons - A Self Defence Guide

Description

Tim Harword, Financial Times, gives a talk for the Reuters Seminar Series. Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/License

http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Site sourced from

http://mediapub.it.ox.ac.uk/feeds/129029/audio.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataAndy Field on teaching quantitative methods to social science students

Description

Andy Field (University of Sussex) discusses his experiences and views of what works well when teaching quantitative methods to undergraduate social science students, especially with mixed ability and low motivation students. Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Subjects

sociology | quantitative methods | statistics | learning | teaching | Social Sciences | sociology | quantitative methods | statistics | learning | teaching | Social SciencesLicense

http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Site sourced from

http://mediapub.it.ox.ac.uk/feeds/129156/audio.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataManfred te Grotenhuis on teaching quantitative methods to social science students

Description

Manfred te Grotenhuis (Radboud University Nijmegen) discusses his experiences and views of what works well when teaching quantitative methods to undergraduate social science students, especially with mixed ability and low motivation students. Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Subjects

statistics | qualitative research | research methods | quantitative research | sociology | teaching | statistics | qualitative research | research methods | quantitative research | sociology | teachingLicense

http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Site sourced from

http://mediapub.it.ox.ac.uk/feeds/129156/audio.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataPaul Kellstedt on teaching quantitative methods to political science students

Description

Paul Kellstedt discusses his experiences and views of what works well when teaching quantitative methods to undergraduate political science students and other social scientists. Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Subjects

teaching | statistics | social science | political science | quantitative methods | teaching | statistics | social science | political science | quantitative methodsLicense

http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Site sourced from

http://mediapub.it.ox.ac.uk/feeds/129156/audio.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataWhat are the latest trends in migration into and out of the UK? - COMPAS Breakfast Briefing

Description

Sarah Croft (Office for National Statistics) gives a talk for the COMPAS Breakfast Briefing series on December 10th, 2010. Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Subjects

national Office for Statistics | statistics | immigration | society | migration | policy | politics | national Office for Statistics | statistics | immigration | society | migration | policy | politics | 2010-12-10License

http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Site sourced from

http://mediapub.it.ox.ac.uk/feeds/129204/audio.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata14.33 Economics Research and Communication (MIT) 14.33 Economics Research and Communication (MIT)

Description

This course will guide students through the process of forming economic hypotheses, gathering the appropriate data, analyzing them, and effectively communicating their results. All students will be expected to have successfully completed Introduction to Statistical Methods in Economics and Econometrics (or their equivalents) as well as courses in basic microeconomics and macroeconomics. Students may find it useful to take at least one economics field course and perform a UROP before taking this course, but these are not requirements. This course will guide students through the process of forming economic hypotheses, gathering the appropriate data, analyzing them, and effectively communicating their results. All students will be expected to have successfully completed Introduction to Statistical Methods in Economics and Econometrics (or their equivalents) as well as courses in basic microeconomics and macroeconomics. Students may find it useful to take at least one economics field course and perform a UROP before taking this course, but these are not requirements.Subjects

empirical economics | empirical economics | econometrics | econometrics | mathematical economics | mathematical economics | statistics | statistics | Economics | Economics | research | research | communication | communication | hypotheses | hypotheses | data | data | analysis | analysis | results | results | STATA | STATA | data sets | data sets | writing | writingLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata15.075 Applied Statistics (MIT) 15.075 Applied Statistics (MIT)

Description

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), Prof. Gordon Kaufman (MIT), Prof. Jacqueline Telford (Johns Hopkins University), and Prof. Ramón León (University of Tennessee) have made to the course material. 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), Prof. Gordon Kaufman (MIT), Prof. Jacqueline Telford (Johns Hopkins University), and Prof. Ramón León (University of Tennessee) have made to the course material.Subjects

data analysis | data analysis | multiple regression | multiple regression | analysis of variance | analysis of variance | multivariate analysis | multivariate analysis | data mining | data mining | probability | probability | collecting data | collecting data | sampling distributions | sampling distributions | inference | inference | linear regression | linear regression | ANOVA | ANOVA | nonparametric methods | nonparametric methods | polls | polls | surveys | surveys | statistics | statistics | management science | management science | finance | finance | statistical graphics | statistical graphics | estimation | estimation | hypothesis testing | hypothesis testing | logistic regression | logistic regression | contingency tables | contingency tables | forecasting | forecasting | factor analysis | factor analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata14.661 Labor Economics I (MIT) 14.661 Labor Economics I (MIT)

Description

Neoclassical analysis of the labor market and its institutions. A systematic development of the theory of labor supply, labor demand, and human capital. Topics discussed also include wage and employment determination, turnover, search, immigration, unemployment, equalizing differences, and institutions in the labor market. There is particular emphasis on the interaction of theoretical and empirical modeling and the development of independent research interests. Neoclassical analysis of the labor market and its institutions. A systematic development of the theory of labor supply, labor demand, and human capital. Topics discussed also include wage and employment determination, turnover, search, immigration, unemployment, equalizing differences, and institutions in the labor market. There is particular emphasis on the interaction of theoretical and empirical modeling and the development of independent research interests.Subjects

labor economics | public policy | schooling | learning | matching | experience | wages | minimum wage | college | investment | training | firms | corporations | labor | unions | panel data | neoclassical model | turnover models | turnover | economics | labor economics | public policy | schooling | learning | matching | experience | wages | minimum wage | college | investment | training | firms | corporations | labor | unions | panel data | neoclassical model | turnover models | turnover | economics | labor | labor | market | market | statistics | statistics | theory | theory | neoclassical | neoclassical | supply | supply | model | model | life-cycle | life-cycle | demand | demand | wages | wages | immigration | immigration | human capital | human capital | econometrics | econometrics | liquidity | liquidity | constraints | constraints | mobility | mobility | incentives | incentives | organization | organization | moral hazard | moral hazard | insurance | insurance | investments | investments | efficiency | efficiency | unemployment | unemployment | search | search | jobs | jobs | training | training | capital | capital | firm | firm | technology | technology | skills | skills | risk | risk | signaling | signaling | discrimination | discrimination | self-selection | self-selection | learning | learning | natives | nativesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataDescription

This is a seminar based on research literature. Papers covered are selected to illustrate important problems and approaches in the field of computational and systems biology, and provide students a framework from which to evaluate new developments. The MIT Initiative in Computational and Systems Biology (CSBi) is a campus-wide research and education program that links biology, engineering, and computer science in a multidisciplinary approach to the systematic analysis and modeling of complex biological phenomena. This course is one of a series of core subjects offered through the CSB PhD program, for students with an interest in interdisciplinary training and research in the area of computational and systems biology. Acknowledgments In addition to the staff listed on this page, the followi This is a seminar based on research literature. Papers covered are selected to illustrate important problems and approaches in the field of computational and systems biology, and provide students a framework from which to evaluate new developments. The MIT Initiative in Computational and Systems Biology (CSBi) is a campus-wide research and education program that links biology, engineering, and computer science in a multidisciplinary approach to the systematic analysis and modeling of complex biological phenomena. This course is one of a series of core subjects offered through the CSB PhD program, for students with an interest in interdisciplinary training and research in the area of computational and systems biology. Acknowledgments In addition to the staff listed on this page, the followiSubjects

computational | computational | systems | systems | biology | biology | seminar | seminar | literature review | literature review | statistics | statistics | developmental | developmental | biochemistry | biochemistry | genetics | genetics | physics | physics | genomics | genomics | signal transduction | signal transduction | regulation | regulation | medicine | medicine | kinetics | kinetics | protein structure | protein structure | devices | devices | synthesis | synthesis | networks | networks | mapping | mappingLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata17.869 Political Science Scope and Methods (MIT) 17.869 Political Science Scope and Methods (MIT)

Description

This course is designed to provide an introduction to a variety of empirical research methods used by political scientists. The primary aims of the course are to make you a more sophisticated consumer of diverse empirical research and to allow you to conduct sophisticated independent work in your junior and senior years. This is not a course in data analysis. Rather, it is a course on how to approach political science research. This course is designed to provide an introduction to a variety of empirical research methods used by political scientists. The primary aims of the course are to make you a more sophisticated consumer of diverse empirical research and to allow you to conduct sophisticated independent work in your junior and senior years. This is not a course in data analysis. Rather, it is a course on how to approach political science research.Subjects

political science | political science | empirical research | empirical research | scientific method | scientific method | research design | research design | models | models | samping | samping | statistical analysis | statistical analysis | measurement | measurement | ethics | ethics | empirical | empirical | research | research | scientific | scientific | methods | methods | statistics | statistics | statistical | statistical | analysis | analysis | political | political | politics | politics | science | science | design | design | sampling | sampling | theoretical | theoretical | observation | observation | data | data | case studies | case studies | cases | cases | empirical research methods | empirical research methods | political scientists | political scientists | empirical analysis | empirical analysis | theoretical analysis | theoretical analysis | research projects | research projects | department faculty | department faculty | inference | inference | writing | writing | revision | revision | oral presentations | oral presentations | experimental method | experimental method | theories | theories | political implications | political implicationsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata6.094 Introduction to MATLABĀ® (MIT) 6.094 Introduction to MATLABĀ® (MIT)

Description

This course provides an aggressively gentle introduction to MATLAB®. It is designed to give students fluency in MATLAB, including popular toolboxes. The course consists of interactive lectures with a computer running MATLAB for each student. Problem-based MATLAB assignments are given which require significant time on MATLAB. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month. This course provides an aggressively gentle introduction to MATLAB®. It is designed to give students fluency in MATLAB, including popular toolboxes. The course consists of interactive lectures with a computer running MATLAB for each student. Problem-based MATLAB assignments are given which require significant time on MATLAB. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.Subjects

matlab | matlab | simulink | simulink | matlab programming | matlab programming | variables | variables | plotting | plotting | scripts | scripts | functions | functions | flow control | flow control | linear algebra | linear algebra | polynomials | polynomials | optimization | optimization | differential equations | differential equations | ode | ode | probability | probability | statistics | statistics | data structures | data structures | images | images | animation | animation | debugging | debugging | symbolic math | symbolic math | toolboxes | toolboxes | scope | scope | function block | function block | nervous system | nervous systemLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataDescription

This course develops logical, empirically based arguments using statistical techniques and analytic methods. It covers elementary statistics, probability, and other types of quantitative reasoning useful for description, estimation, comparison, and explanation. Emphasis is placed on the use and limitations of analytical techniques in planning practice. This course is required for and restricted to first-year Master in City Planning students. This course develops logical, empirically based arguments using statistical techniques and analytic methods. It covers elementary statistics, probability, and other types of quantitative reasoning useful for description, estimation, comparison, and explanation. Emphasis is placed on the use and limitations of analytical techniques in planning practice. This course is required for and restricted to first-year Master in City Planning students.Subjects

statistics | statistics | statistical methods | statistical methods | quantitative research | quantitative research | argument | argument | measurement | measurement | research design | research design | frequency distribution | frequency distribution | histogram | histogram | stemplot | stemplot | boxplot | boxplot | dispersion | dispersion | probability | probability | normal distribution | normal distribution | binomial distribution | binomial distribution | sampling | sampling | confidence interval | confidence interval | significance | significance | correlation | correlation | regression | regressionLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadataDescription

This course will provide a solid foundation in probability and statistics for economists and other social scientists. We will emphasize topics needed in the further study of econometrics and provide basic preparation for 14.32. No prior preparation in probability and statistics is required, but familiarity with basic algebra and calculus is assumed. This course will provide a solid foundation in probability and statistics for economists and other social scientists. We will emphasize topics needed in the further study of econometrics and provide basic preparation for 14.32. No prior preparation in probability and statistics is required, but familiarity with basic algebra and calculus is assumed.Subjects

Economics | Economics | statistics | statistics | methods | methods | probability | probability | economists | economists | social scientists | social scientists | econometrics | econometrics | algebra | algebra | calculus | calculusLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata12.740 Paleoceanography (MIT) 12.740 Paleoceanography (MIT)

Description

This class examines tools, data, and ideas related to past climate changes as seen in marine, ice core, and continental records. The most recent climate changes (mainly the past 500,000 years, ranging up to about 2 million years ago) will be emphasized. Quantitative tools for the examination of paleoceanographic data will be introduced (statistics, factor analysis, time series analysis, simple climatology). This class examines tools, data, and ideas related to past climate changes as seen in marine, ice core, and continental records. The most recent climate changes (mainly the past 500,000 years, ranging up to about 2 million years ago) will be emphasized. Quantitative tools for the examination of paleoceanographic data will be introduced (statistics, factor analysis, time series analysis, simple climatology).Subjects

history of the earth-surface environment | history of the earth-surface environment | deep-sea sediments | deep-sea sediments | ice cores | ice cores | corals | corals | Micropaleontological | Micropaleontological | isotopic | isotopic | geochemical | and mineralogical changes | geochemical | and mineralogical changes | seawater composition | seawater composition | atmospheric chemistry | atmospheric chemistry | climate | climate | ocean temperature | ocean temperature | circulation | circulation | chemistry | chemistry | glacial/interglacial cycles | glacial/interglacial cycles | orbital forcing | orbital forcing | climate change | climate change | marine records | marine records | ice core records | ice core records | continental records | continental records | paleoceanographic data | paleoceanographic data | statistics | statistics | factor analysis | factor analysis | time series analysis | time series analysis | simple climatology | simple climatology | geochemical changes | geochemical changes | mineralogical changes | mineralogical changes | glacial cycles | glacial cycles | intergalacial cycles | intergalacial cycles | earth-surface environment | earth-surface environment | environmental history | environmental history | Oxygen Isotope | Oxygen Isotope | Coral Reefs | Coral Reefs | Paleoceanography | Paleoceanography | Paleoclimatology | Paleoclimatology | Paleothermometry | Paleothermometry | Atmospheric Carbon Dioxide | Atmospheric Carbon Dioxide | Ocean Chemistry | Ocean Chemistry | Salinity | SalinityLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata1.010 Uncertainty in Engineering (MIT) 1.010 Uncertainty in Engineering (MIT)

Description

This undergraduate class serves as an introduction to probability and statistics, with emphasis on engineering applications. The first segment discusses events and their probability, Bayes' Theorem, discrete and continuous random variables and vectors, univariate and multivariate distributions, Bernoulli trials and Poisson point processes, and full-distribution uncertainty propagation and conditional analysis. The second segment deals with second-moment representation of uncertainty and second-moment uncertainty propagation and conditional analysis. The final segment covers random sampling, point and interval estimation, hypothesis testing, and linear regression. Many of the concepts covered in class are illustrated with real-world examples from various areas of engineering. This undergraduate class serves as an introduction to probability and statistics, with emphasis on engineering applications. The first segment discusses events and their probability, Bayes' Theorem, discrete and continuous random variables and vectors, univariate and multivariate distributions, Bernoulli trials and Poisson point processes, and full-distribution uncertainty propagation and conditional analysis. The second segment deals with second-moment representation of uncertainty and second-moment uncertainty propagation and conditional analysis. The final segment covers random sampling, point and interval estimation, hypothesis testing, and linear regression. Many of the concepts covered in class are illustrated with real-world examples from various areas of engineering.Subjects

statistics | statistics | decision analysis | decision analysis | random variables and vectors | random variables and vectors | uncertainty propagation | uncertainty propagation | conditional distributions | conditional distributions | second-moment analysis | second-moment analysis | system reliability | system reliability | Bayesian analysis and risk-based decision | Bayesian analysis and risk-based decision | estimation of distribution parameters | estimation of distribution parameters | hypothesis testing | hypothesis testing | simple and multiple linear regressions | simple and multiple linear regressions | Poisson and Markov processes | Poisson and Markov processesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata