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Consider a binary response variable y and an
explanatory variable x that varies between 0 and 4. The
linear model is estimated as yˆy^ = −1.19 +
0.53x.
a. Compute the estimated probability for
x = 2 and x = 3. (Negative values
should be indicated by a minus sign. Round your answers to 2
decimal places.)
b. For what values of x is the estimated probability negative or greater than one? (Round your answers to 2 decimal places.)
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y^ = -1.19 + 0.53 * x
a) x = 2
y^ = -1.19 + 0.53 * 2 = -0.13 (ans)
x = 3
y^ = -1.19 + 0.53 * 3 = 0.4
b) Estimated probability negative,
y^ < 0
or, -1.19 + 0.53 * x < 0
or, 0.53 * x < 1.19
or, x < 2.25 (ans)
Estimated probability greater than one,
y^ > 1
or, -1.19 + 0.53 * x > 1
or, 0.53 * x > 1 + 1.19
or, x > 4.13 (ans)
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Can someone help me with the work either by hand or using R?
Thanks!
Consider a binary response variable y and an
explanatory variable x. The following table contains the
parameter estimates of the linear probability model (LPM) and the
logit model, with the associated p-values shown in
parentheses.
Variable
LPM
Logit
Constant
−0.69
−6.30
(0.06)
(0.06)
x
0.06
0.21
(0.04)
(0.06)
a. Test for the significance of the intercept and
the slope coefficients at the 5% level in both...
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