Model Equation:

    Water = - 122 + 1.51*Temperature + 12.5*Mowing Time

• Intercept = b(0) = -121.655

• Temperature = b(1) = 1.512364

• Mowing Time = b(2) = 12.53168

• Standard Error = s{b(k)}

  • s{b(0)} = 6.540348

  • s{b(1)} = .060771

  • s{b(2)} = 1.93302

For Testing B(k):

    test statistic

*using your own t-table with in each tail and df = (n-p) = (7-4).

For B(0):

• t(0) = -121.655 = -18.6007 (t Stat)
            6.540348

• P-value = 4.92E-05 = .0000492

  • Remember MS Excel uses scientific notation.

  • Click here for a p-value review.

• Conclusion for B(0):

  • Reject H(0): There is significant evidence to conclude that b(0) should not be dropped from the model.

For B(1):

• t(1) = 1.512364 = 24.88626 (t Stat)
            .060771

• P-value = 1.55E-05 = .0000155

  • Remember MS Excel uses scientific notation.

  • Click here for a p-value review.

• Conclusion for B(1):

  • Reject H(0): There is significant evidence to conclude that b(1) should not be dropped from the model.

For B(2):

• t(2) = 12.53168 = 6.482954 (t Stat)
            1.93302

• P-value = .002918

  • Click here for a p-value review.

• Conclusion for B(2):

  • Reject H(0): There is significant evidence to conclude that b(2) should not be dropped from the model.

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