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# Conduct a regression model for the following equation.

INSTRUCTIONS TO CANDIDATES

trying to get this code completed in Python #

Q2.3. Conduct a regression model for the following equation. # Y = b0 + a X1 + b X2 where Y is Return, X1 is PE Ratio, and X2 is Risk.

# In[ ]: Y = df[PE] X = df[Return] result = smf.ols(formula = '?', data = df).fit() print(result.summary()) print(result.params)

# Q2.4: Conduct a regression model for the following equation. # Y = b0 + a X1 + b X2 + c X3 + d X4 # where Y is Return, X1 is PE Ratio, and X2 is Risk, X3 is X1 ^2 and X4 is X2^2

# In[ ]: Y = df['Return']

# add a new column called 'X3' whoch is Risk^2 df['X3'] = pd.'?(df'?') # add a new column called 'X4' whoch is Risk^2 df['X4'] = pd.'?'(df'?') X = df[[?]] result = smf.ols(formula = '?', data = df).fit() print(result.summary()) print(result.params)

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