Update pages/5_Descriptive Statistics.py

pages/5_Descriptive Statistics.py

@@ -242,4 +242,40 @@ Q_3 \text{ is the third quartile (75th percentile)}
 ''')
 st.latex(r'''
 Q_1 \text{ is the first quartile (25th percentile)}
-''')
+''')
+st.subheader("Quartile Deviation",divider="violet")
+multi = '''Quartile deviation is inter-quartile range divided by two .
+Inter-quartile range is difference between upper quartile and lower quartile in the distribution.
+IQR is to know the central 50% tendency value
+
+Interquartile Range = Upper Quartile (Q3)–Lower Quartile(Q1)
+It is known as Semi-Inter-Quartile Range i.e. half of the difference between the upper quartile and lower quartile'''
+st.markdown(multi)
+
+st.latex(r'''
+\text{Quartile Deviation} = \frac{Q_3 - Q_1}{2}
+''')
+
+st.write("Where:")
+st.latex(r'''
+Q_3 \text{ is the third quartile (75th percentile)}
+''')
+st.latex(r'''
+Q_1 \text{ is the first quartile (25th percentile)}
+''')
+
+multi = '''Quartile deviation only gives central 50% values that are close to median or not (it basically gives the behaviour of central data).
+
+--->**More the spread then the deviation is high**
+--->**spread is directly proportional to deviation**
+
+Quartile deviation has some basic terms:
+:red[Quantile]:To summarize the central tendency or dispersion - when quantiles(values) are dividing the data into equal parts then the part of dividing into equal parts are quantiles which are of 3 types
+
+There are 3 types of quantile which divide the data:
+:violet[1.Quartile]: divides the data into 4 equal parts 
+:violet[2.Percentile]: when the data is going to divide into 100 equal parts that particular quantile is known as percentile
+:violet[3.Decile]:when the data is going to divide into 10 equal parts that particular quantile is known as decile 
+'''
+st.markdown(multi)
+