Answer:
Quadrant I and III
Step-by-step explanation:
The coordinate (3,9) is all positive, therefore it lies in quadrant I.
The coordinate (-3,-9) is all negative, therefore it lies in quadrant III.
Answer:
A Type II error is when the null hypothesis is failed to be rejected even when the alternative hypothesis is true.
In this case, it would represent that the new program really increases the pass rate, but the sample taken is not enough statistical evidence to prove it. Then, the null hypothesis is not rejected.
The consequence is that the new method would be discarded (or changed) eventhough it is a real improvement.
Step-by-step explanation:
Answer:
Null Hypothesis: H_0: \mu_A =\mu _B or \mu_A -\mu _B=0
Alternate Hypothesis: H_1: \mu_A >\mu _B or \mu_A -\mu _B>0
Here to test Fertilizer A height is greater than Fertilizer B
Two Sample T Test:
t=\frac{X_1-X_2}{\sqrt{S_p^2(1/n_1+1/n_2)}}
Where S_p^2=\frac{(n_1-1)S_1^2+(n_2-1)S_2^2}{n_1+n_2-2}
S_p^2=\frac{(14)0.25^2+(12)0.2^2}{15+13-2}= 0.0521154
t=\frac{12.92-12.63}{\sqrt{0.0521154(1/15+1/13)}}= 3.3524
P value for Test Statistic of P(3.3524,26) = 0.0012
df = n1+n2-2 = 26
Critical value of P : t_{0.025,26}=2.05553
We can conclude that Test statistic is significant. Sufficient evidence to prove that we can Reject Null hypothesis and can say Fertilizer A is greater than Fertilizer B.
I believe the correct answers are:
<span>UV = 14 ft and m∠TUV = 45°</span>
<span>ST = 20 ft, UV = 14 ft, and m∠UST = 98°
Or, in other words, Options A and D.
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