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  4. Correlation and Regression Lines - A Quick Recap #4
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Correlation and Regression Lines - A Quick Recap #4

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  • andrew_katoch
     + 0 comments

    Solving for x using the first equation is correct, but not the second. Why is that? I assume it has to do with the line _ on _ but I don't get why

  • Daigann
     + 0 comments

    Here is the code in Python 3:

    # estimate the value of x when y = 7
y = 7

# the regression line 
val_x = (9 * y + 107) / 20

# print the result
print(round(val_x, 1))

  • aurthur01
     + 0 comments

    x=[i for i in range(0,20)]

    ''' 4x - 5y + 33 = 0 x = ( 5y - 33 ) / 4 y = ( 4x + 33 ) / 5

    20x - 9y - 107 = 0
x = (9y + 107)/20
y = (20x - 107)/9

    ''' t=7 print( ( 9 * t + 107 ) / 20 )

  • vai_suliafu
     + 0 comments

    It's very simple. They are giving two different regression equations just to ensure you pick the correct one. Since we are given a value of 'y' and are asked to estimate a value of 'x', we need to pick the equation for 'y regressed on x'. Then you just need to plug in your value for y and solve for x.

  • jane_renjing
     + 0 comments

    As I understand it, there could be a third variable (which is dependent on both x and y) involved implicitly, which is why we get two regression results?