notes.out

\BOOKMARK [1][-]{section.1}{Estimate coefficient and Variance of Coefficient in Linear Regression}{}% 1
\BOOKMARK [2][-]{subsection.1.1}{Best Estimate of Coefficient}{section.1}% 2
\BOOKMARK [2][-]{subsection.1.2}{Variance of Coefficient}{section.1}% 3
\BOOKMARK [1][-]{section.2}{Estimate coefficient and Variance using Matrix Approach}{}% 4
\BOOKMARK [1][-]{section.3}{Cross-Validation}{}% 5
\BOOKMARK [1][-]{section.4}{Bootstrapping}{}% 6
\BOOKMARK [1][-]{section.5}{Adaboost or Boosted Decision Trees}{}% 7
\BOOKMARK [1][-]{section.6}{Random Forest}{}% 8
\BOOKMARK [1][-]{section.7}{Numpy: Argpartition and Partition}{}% 9
\BOOKMARK [2][-]{subsection.7.1}{Partition}{section.7}% 10
\BOOKMARK [2][-]{subsection.7.2}{Argpartition}{section.7}% 11
\BOOKMARK [1][-]{section.8}{Lists and Tuples}{}% 12
\BOOKMARK [1][-]{section.9}{np.c}{}% 13
\BOOKMARK [1][-]{section.10}{Standard Error, Root Mean Square Error, Standard Deviation}{}% 14
\BOOKMARK [1][-]{section.11}{Identification of Outliers using Studentized Residuals}{}% 15
\BOOKMARK [1][-]{section.12}{1-sigma interpretation}{}% 16
\BOOKMARK [1][-]{section.13}{Correlation and Covariance}{}% 17
\BOOKMARK [1][-]{section.14}{Null hypothesis, P-Value and Pearson's Chi-square test}{}% 18
\BOOKMARK [1][-]{section.15}{Groupby in Pandas}{}% 19
\BOOKMARK [1][-]{section.16}{A/B Testing and Null Hypothesis}{}% 20
\BOOKMARK [1][-]{section.17}{Lagrange Multiplier}{}% 21
\BOOKMARK [1][-]{section.18}{Confidence Interval and Margin of Error}{}% 22