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Introduction to Statistical Computing
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Learning Material
Title
Volume
Introduction to R: Basic commands and syntax, object types, data import/export.
5.89 MB
<p>Introduction to R: Basic commands and syntax, object types, data import/export.</p>
Descriptive Statistics: Mean, median, variance, standard deviation, graphical representation.
5.89 MB
<p>Descriptive Statistics: Mean, median, variance, standard deviation, graphical representation.</p>
Probability: Basic probability concepts, probability distributions, random variables.
5.89 MB
<p>Probability: Basic probability concepts, probability distributions, random variables.</p>
Inferential Statistics: Confidence intervals, hypothesis testing, p-values.
5.89 MB
<p>Inferential Statistics: Confidence intervals, hypothesis testing, p-values.</p>
Linear Regression: Simple linear regression, multiple linear regression.
5.89 MB
<p>Linear Regression: Simple linear regression, multiple linear regression.</p>
Data Visualization: Scatter plots, line plots, bar plots, histograms, box plots.
5.89 MB
<p>Data Visualization: Scatter plots, line plots, bar plots, histograms, box plots.</p>
Data Manipulation: Sorting, filtering, summarizing, merging, reshaping datasets.
5.89 MB
<p>Data Manipulation: Sorting, filtering, summarizing, merging, reshaping datasets.</p>
Introduction to Machine Learning: Overview of machine learning, basic concepts, supervised vs. unsupervised learning.
5.89 MB
<p>Introduction to Machine Learning: Overview of machine learning, basic concepts, supervised vs. unsupervised learning.</p>
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