15.075 Applied Statistics, Spring 2003
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 pro...
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| Format: | Learning Object |
| Language: | en-US |
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2003
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| Online Access: | http://hdl.handle.net/1721.1/72947 |
| _version_ | 1824458053039161344 |
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| author | Newton, Elizabeth |
| author2 | Sloan School of Management |
| author_facet | Sloan School of Management Newton, Elizabeth |
| author_sort | Newton, Elizabeth |
| collection | 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. |
| first_indexed | 2024-09-23T10:42:39Z |
| format | Learning Object |
| id | mit-1721.1/72947 |
| institution | Massachusetts Institute of Technology |
| language | en-US |
| last_indexed | 2025-02-19T04:19:46Z |
| publishDate | 2003 |
| record_format | dspace |
| spelling | mit-1721.1/729472025-02-18T16:34:49Z 15.075 Applied Statistics, Spring 2003 Applied Statistics Newton, Elizabeth Sloan School of Management data analysis multiple regression analysis of variance multivariate analysis data mining probability collecting data sampling distributions inference linear regression ANOVA nonparametric methods polls surveys statistics management science finance statistical graphics estimation hypothesis testing logistic regression contingency tables forecasting factor analysis Statistics 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. 2003-06 Learning Object 15.075-Spring2003 local: 15.075 local: IMSCP-MD5-3b7fefac0fd6863a1a5fe7fe205f459f http://hdl.handle.net/1721.1/72947 en-US Usage Restrictions: This site (c) Massachusetts Institute of Technology 2012. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license") unless otherwise noted. The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions. text/html Spring 2003 |
| spellingShingle | data analysis multiple regression analysis of variance multivariate analysis data mining probability collecting data sampling distributions inference linear regression ANOVA nonparametric methods polls surveys statistics management science finance statistical graphics estimation hypothesis testing logistic regression contingency tables forecasting factor analysis Statistics Newton, Elizabeth 15.075 Applied Statistics, Spring 2003 |
| title | 15.075 Applied Statistics, Spring 2003 |
| title_full | 15.075 Applied Statistics, Spring 2003 |
| title_fullStr | 15.075 Applied Statistics, Spring 2003 |
| title_full_unstemmed | 15.075 Applied Statistics, Spring 2003 |
| title_short | 15.075 Applied Statistics, Spring 2003 |
| title_sort | 15 075 applied statistics spring 2003 |
| topic | data analysis multiple regression analysis of variance multivariate analysis data mining probability collecting data sampling distributions inference linear regression ANOVA nonparametric methods polls surveys statistics management science finance statistical graphics estimation hypothesis testing logistic regression contingency tables forecasting factor analysis Statistics |
| url | http://hdl.handle.net/1721.1/72947 |
| work_keys_str_mv | AT newtonelizabeth 15075appliedstatisticsspring2003 AT newtonelizabeth appliedstatistics |