Statistics for Data Science

The objective of the course is to introduce the statistical methods, techniques and tools that are essential for Data science domain. The course focuses on examining descriptive and inferential statistics and analyzing The output of these methods. The course also emphasizes techniques for result estimation and anomaly detection. Statistical machine learning methods that "learn" from data will be also introduced.

Name		Name	Last commit message	Last commit date
Latest commit History 28 Commits
00_Python_Basics.ipynb		00_Python_Basics.ipynb
01_Numpy_Arrays_and_Pandas_DataFrames.ipynb		01_Numpy_Arrays_and_Pandas_DataFrames.ipynb
02_CSE303_Lab01.ipynb		02_CSE303_Lab01.ipynb
03_CSE303_Lab02_Practice.ipynb		03_CSE303_Lab02_Practice.ipynb
04_Lab_Assignment_Lab02.ipynb		04_Lab_Assignment_Lab02.ipynb
05_CSE303_Lab03_Practice_.ipynb		05_CSE303_Lab03_Practice_.ipynb
06_Lab_Assignment_Lab03.ipynb		06_Lab_Assignment_Lab03.ipynb
07_CSE303_Lab04_Practice.ipynb		07_CSE303_Lab04_Practice.ipynb
08_Lab_Assignment_Lab04.ipynb		08_Lab_Assignment_Lab04.ipynb
09_CSE303_Lab05_Practice.ipynb		09_CSE303_Lab05_Practice.ipynb
10_CSE303_Lab06_Practice.ipynb		10_CSE303_Lab06_Practice.ipynb
11_CSE303_Lab07_Practice.ipynb		11_CSE303_Lab07_Practice.ipynb
12_CSE303_Lab8_Practice.ipynb		12_CSE303_Lab8_Practice.ipynb
13_CSE303_Lab09_Practice.ipynb		13_CSE303_Lab09_Practice.ipynb
14_Lab_Quiz.ipynb		14_Lab_Quiz.ipynb
Boston.csv		Boston.csv
LICENSE.txt		LICENSE.txt
README.md		README.md
cereal.csv		cereal.csv
dataset1_lab02.csv		dataset1_lab02.csv
dataset_multiple_LR.xlsx		dataset_multiple_LR.xlsx
iris-data.csv		iris-data.csv
random number csv file generator.py		random number csv file generator.py
surveys.csv		surveys.csv
titanic_train.csv		titanic_train.csv
weather.csv		weather.csv

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