Answer:
Step-by-step explanation:
In the model
Log (salary) = B0 + B1LSAT +B2GPA +B3log(libvol) +B4log(cost)+B5 rank+u
The hypothesis that rank has no effect on log (salary) is H0:B5 = 0. The estimated equation (now with standard errors) is
Log (salary) = 8.34 + .0047 LSAT + .248 GPA + .095 log(libvol)
(0.53) (.0040) (.090) (.033)
+ .038 log(cost) – .0033 rank
(.032) (.0003)
n = 136, R2 = .842.
The t statistic on rank is –11(i.e. 0.0033/0.0003), which is very significant. If rank decreases by 10 (which is a move up for a law school), median starting salary is predicted to increase by about 3.3%.
(ii) LSAT is not statistically significant (t statistic ≈1.18) but GPA is very significance (t statistic ≈2.76). The test for joint significance is moot given that GPA is so significant, but for completeness the F statistic is about 9.95 (with 2 and 130 df) and p-value ≈.0001.
Answer:
Step-by-step explanation:
30. Given: rectangles QRST and RKST
Prove: ΔQSK is isosceles
An isosceles triangle is a triangle which has two sides and two angles to be equal.
Thus,
From rectangle QRST, the diagonals of rectangles are similar.
i.e RT ≅ QS (diagonal property)
Also, RT ≅ SK (opposite sides of rectangle RKST)
Thus,
RT ≅ QS ≅ SK
Therefore,
ΔQSK is an isosceles triangle.
31. Given: Rectangles QRST, RKST and JQST
Prove: JT ≅ KS
From rectangle QRST, the diagonals of rectangles are similar.
i.e RT ≅ QS (diagonal property)
But,
JT // QS and RT // KS
Thus,
JT ≅ QS (opposite sides of rectangle JQST)
also,
RT ≅ KS (opposite sides of rectangle RKST)
So that,
JT ≅ QS ≅ RT ≅ KS
Therefore,
JT ≅ KS
Answer:
-35h-42
Step-by-step explanation:
Just multiply 7 into the parentheses and you will get the answer
Ask if you have any questions!
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