1. The fact that heights are known to be normally distributed is important in this test because: O this is a Z-test O both standard deviations are less than thirty O both sample sizes are less than thirty O this is a T-test The hypotheses are: O Ho:µi < µ2; Ha:µ1 > µ2 O Ho:p1 = p2; Ha:pi # p2 O Ho:p1 2 p2; Ha:p1 < P2 O Ho:p = µ2; Ha:µ # Hz O Ho:p < P2; Ha:p, > p2 O Ho: 2 pz; Ha:µ < µz

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* HW 10.1,10.2
A Ideas for Literature Review
l, Search Results
ge.instructure.com/courses/2177802/assignments/13744575
A Maps
Test the claim that on average, heights (in feet) of oak trees in a forest are more than heights of pine
trees. Use a = 0.01.
It is known that tree heights follow a normal distribution.
The table below shows the results of two random samples.
Туре
Oaks
21
88.9
16
Pines
25
70.9
14.7
ne
1. The fact that heights are known to be normally distributed is important in this test because:
O this is a Z-test
O both standard deviations are less than thirty
O both sample sizes are less than thirty
O this is a T-test
pr
The hypotheses are:
O Ho:µ1 < µ2; Ha:µ1 > µ2
O Ho:pi = p2; Ha:pi # p2
O Ho:p, > P2; Ha:p1 < P2
O Ho:µ = µ2; Ha: # Hz
O Ho:p < P2; Ha:p > P2
O Ho: 2 µz; Ha:µ < Hz
2. This is a O rightO twoO left tailed test and the distribution used is
OT since both o values are not known
OZ since testing two proportions
OZ since both o values are known
Transcribed Image Text:* HW 10.1,10.2 A Ideas for Literature Review l, Search Results ge.instructure.com/courses/2177802/assignments/13744575 A Maps Test the claim that on average, heights (in feet) of oak trees in a forest are more than heights of pine trees. Use a = 0.01. It is known that tree heights follow a normal distribution. The table below shows the results of two random samples. Туре Oaks 21 88.9 16 Pines 25 70.9 14.7 ne 1. The fact that heights are known to be normally distributed is important in this test because: O this is a Z-test O both standard deviations are less than thirty O both sample sizes are less than thirty O this is a T-test pr The hypotheses are: O Ho:µ1 < µ2; Ha:µ1 > µ2 O Ho:pi = p2; Ha:pi # p2 O Ho:p, > P2; Ha:p1 < P2 O Ho:µ = µ2; Ha: # Hz O Ho:p < P2; Ha:p > P2 O Ho: 2 µz; Ha:µ < Hz 2. This is a O rightO twoO left tailed test and the distribution used is OT since both o values are not known OZ since testing two proportions OZ since both o values are known
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