Update Introduction_to_Statistics.py

Introduction_to_Statistics.py

@@ -33,4 +33,19 @@ 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.title("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("2.1 Descriptive Statistics",divider=True)
+st.subheader("2.2 Inferential Statistics",divider=True)
+st.subheader("**2.1 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""")
+st.subheader("**2.2 Inferential Statistics**")
+st.markdown("""This Inferential Statistics will describe the population based
+on a sample data. This statistics will give predictions about a population based on sample.
+""")