1.4 The major flaw of the linear probability model is that a. the actuals can on

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1.4 The major flaw of the linear probability model is that a. the actuals can only be 0 and 1, but the predicted are almost always different from that the regreston R2 cannot be tused as a measure of ft c. people do not always make clear-cut decisions predicted values can lie above 1 and below 0 1.5 In the expression , Pr(Y = 11X1) = (Ao + AX) , a. (Bo +BiX) plays the role of z in the cumulative standard normal distribu- tion function. b. cannot be negative since probabilities have to lie between 0 and 1. c.Bo cannot be negative since probabilities have to lie between 0 and 1. d. min (30 + |X) > 0 since probabilities have to lie between 0 and 1. 1.6 In the expression Pr(deny-11 P/I Ratio, black)-9 (-2.26 + 2.74P/I ratio +0.71black), the effect of increasing the P/I ratio from 0.3 to 0.4 for a white person a. is 0.274 percentage points. b. is 6.1 percentage points. c. should not be interpreted without knowledge of the regression R2 d. is 2.74 percentage points.

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1.4) D) the predicted values can lie above 1 and below 0

All other options are not the primary flaws.

But from regression outputs, we see that predicted values vary greatly from below zero to above 1.

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