STATISTICS
Parameter estimation. Maximum likelihood estimation. Confidence intervals. Bayesian estimation. Hypothesis testing. Goodness of fit. The chi-squared test. The t-student test. The F-test. Linear regression. Hypothesis testing in linear models.
Statistics, by R. Weber, 2007, University of Cambridge.
Statistics, by D. Spiegelhalter, 2016, University of Cambridge.
Statistics, written by D. Chua, based on lectures by D. Spiegelhalter, 2015, University of Cambridge.
Statistics, by N. Laws, 2021, University of Oxford.
Statistics, by K. Zhou, Stanford University.
18.443 Statistics for Applications, by P. Kempthorne, 2015, Massachusetts Institute of Technology.
18.443 Statistics for Applications, by D. Panchenko, 2006, Massachusetts Institute of Technology.
18.443 Statistics for Applications, by D. Panchenko, 2003, Massachusetts Institute of Technology.
18.650 Statistics for Applications, by P. Rigollet, 2016, Massachusetts Institute of Technology.
- With Solutions
18.443 Statistics for Applications, by P. Kempthorne, 2015, Massachusetts Institute of Technology. - Without Solutions
Statistics, by R. Weber, 2007, University of Cambridge.
Statistics, by D. Spiegelhalter, 2015, University of Cambridge.
Statistics, by N. Laws, 2021, University of Oxford.
18.443 Statistics for Applications, by D. Panchenko, 2006, Massachusetts Institute of Technology.
18.443 Statistics for Applications, by D. Panchenko, 2003, Massachusetts Institute of Technology.
18.650 Statistics for Applications, by P. Rigollet, 2016, Massachusetts Institute of Technology.
18.650 Statistics for Applications, by P. Rigollet, 2016, Massachusetts Institute of Technology.
Lectures on Statistics, by R. B. Ash, 2007, University of Illinois.
Statistics: Theory and Methods, by D. A. Berry, B. W. Lindgren, 2nd ed., 1995, Duxbury Press.
Schaum’s Outline of Statistics, by Murray Spiegel, L. Stephens, 6th ed., 2017, McGraw Hill.