Update app.py

app.py

@@ -1,5 +1,5 @@
 import streamlit as st
-st.title(":red[**INTRODUCTION TO STATISTICS**]")
+st.title(":red[**1 : INTRODUCTION TO STATISTICS**]")
 st.markdown("""_In this field we will be dealing with data by using programing language python. The term DATA
 ANALYSIS itself say’s that it will be dealing with data. In this we will be collecting the data and
 will be cleaning the data and then we will be analyzing the to get the insights from them. Now
@@ -31,4 +31,15 @@ st.markdown("""This type of data can be called as combination of
 structured data as well as unstructured data. Some of the best examples of semi structured
 data are given below.\n * COMMA SEPERATED VARIABLE\n *JSON FILES\n * E-MAILS\n * HTML
 """)
-st.image("https://cdn-uploads.huggingface.co/production/uploads/64c972774515835c4dadd754/Nupc6BePInRVo9gJwLfWH.png", width=400)
+st.image("https://cdn-uploads.huggingface.co/production/uploads/64c972774515835c4dadd754/Nupc6BePInRVo9gJwLfWH.png", width=400)
+st.tilte("2 : INTRODUCTION TO STATISTICS")
+st.markdown("""_The term statistics is a branch of mathematics and also can be called as a huge field in which
+we are going to deal with data which involves collecting, analyzing, interpreting, and
+structuring the data. Statistics is classified into two types.
+_""")
+st.subheader("Descriptive Statistics",divider=True)
+st.subheader("Inferential Statistics",divider=True)
+st.subheader("**Descriptive Statistics**")
+st.markdown("This Descriptive Statistics describe the main feature of data. This
+descriptive statistics can be performed on sample data as well as population data. Some of
+the key points of descriptive statistics are stated below.\n ** KEY COCEPTS\n * Measurement of Central Tendency which involves finding Mean, Median, and Mode.\n * Measurement of Dispersion which involves finding Range, Variance and Standard Deviation.\n * Distribution which gives how frequently the data is occurring some of examples of distribution are Gaussian, Random, and Normal distribution")