Update app.py

app.py

@@ -39,9 +39,9 @@ st.markdown("""_The term statistics is a branch of mathematics and also can be c
 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.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""")
@@ -292,7 +292,7 @@ st.markdown(''':blue[**Distribution**] is a measure will will tell how the shape
 analysis.There are few types of distribution \n *  Normal Distribution \n * Uniform Distribution \n * Binomial Distribution \n * Poisson Distribution
 \n * Exponential Distribution \n * Chi-Square Distribution \n * T-Distribution
 ''')
-st.subheader("**Inferential Statistics**")
+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.
 """)