Introduction

In this statistical analysis project, we will work on a diamond dataset that contains diamond price, table, depth, x-y-z dimensions, color, clarity, cut quality, and carat.

We will first perform descriptive analysis on some of the features by calculating its central tendency and dispersion. Then we will perform regression on diamond price using multiple techniques and approaches and compare their performance, We will use linear regression to predict the diamond's price And Finally, we will attempt to classify the clarity of the diamond based on its other features.

the dataset used can be found here: https://www.kaggle.com/shivam2503/diamonds

Files and their functions

Final report -

Diamond Analysis.pdf

Statistical analysis and Data cleaning -

notebook.ipynb

Statistical analysis and Data cleaning -

notebook.ipynb

Diamond's price prediction using tensorflow

diamond price regression with tensorflow.ipynb

Diamond's price prediction using correlation coefficient

diamond price regression using correlation coefficient.ipynb

Diamond's dimension regression using correlation coefficient

diamond dimension regression using correlation coefficient.ipynb