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Update pages/5_Descriptive Statistics.py
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pages/5_Descriptive Statistics.py
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@@ -311,7 +311,8 @@ st.latex(r'''
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\text{Coefficient of Quartile Deviation} = (\frac{Q_3 - Q_1}{Q_3 + Q_1})*100''')
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st.subheader("Variance",divider="violet")
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multi = '''Variance is used for measuring the dispersion or spread.Average of spread or dispersion is known as variance.
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st.markdown(multi)
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st.latex(r'''
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\sigma^2 = \frac{\sum (X_i - \mu)^2}{N}''')
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@@ -347,9 +348,7 @@ multi = '''Variance can't be easily interpreted because we are doubling the devi
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--->**More the spread it means more the standard deviation**
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--->**spread is directly proportional to the standard deviation**
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--->to check the consistency of data co-efficient of variance is used'''
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st.markdown(multi)
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st.latex(r'''
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\sigma = \sqrt{\frac{\sum (X_i - \mu)^2}{N}}''')
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@@ -378,6 +377,12 @@ st.subheader("Sample standard deviation")
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st.latex(r'''
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s = \sqrt{\frac{\sum (X_i - \bar{X})^2}{n - 1}}''')
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multi = '''--->σ is the population standard deviation
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--->s is the sample standard deviation
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@@ -391,4 +396,5 @@ multi = '''--->σ is the population standard deviation
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--->N is the total number of data points in the population
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--->n is the number of data points in the sample.'''
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st.markdown(multi)
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\text{Coefficient of Quartile Deviation} = (\frac{Q_3 - Q_1}{Q_3 + Q_1})*100''')
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st.subheader("Variance",divider="violet")
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multi = '''Variance is used for measuring the dispersion or spread.Average of spread or dispersion is known as variance.
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-->to check the consistency of data co-efficient of variance is used'''
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st.markdown(multi)
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st.latex(r'''
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\sigma^2 = \frac{\sum (X_i - \mu)^2}{N}''')
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--->**More the spread it means more the standard deviation**
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--->**spread is directly proportional to the standard deviation**'''
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st.markdown(multi)
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st.latex(r'''
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\sigma = \sqrt{\frac{\sum (X_i - \mu)^2}{N}}''')
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st.latex(r'''
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s = \sqrt{\frac{\sum (X_i - \bar{X})^2}{n - 1}}''')
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st.latex(r'''
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\text{Population Coefficient of Standard Deviation} = \frac{\sigma}{\mu}''')
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st.latex(r'''
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\text{Sample Coefficient of Standard Deviation} = \frac{s}{\bar{X}}''')
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multi = '''--->σ is the population standard deviation
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--->s is the sample standard deviation
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--->N is the total number of data points in the population
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--->n is the number of data points in the sample.'''
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st.markdown(multi)
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