Answer:
henc X = 30°
Step-by-step explanation:
here is the proof
when X=30° then
sin2x = sin2×30
=sin 60°
= √3/2
or else,
putting value of X = 30° then
sin2x= 2sinxcosx
= 2×sin30°×cos30°
=2×1/2×√3/2
= 2√3/4
= √3/2
hence proved sin2x= √3/2.
Answer:
i believe it's 18
Step-by-step explanation:
9/6=1.5
27/1.5= 18
Complete Question
The complete question is shown on the first uploaded image
Answer:
a
Yes the researcher can conclude that the supplement has a significant effect on cognitive skill
b

c
The result of this hypothesis test shows that there is sufficient evidence to that the supplement had significant effect.The measure of effect size is large due to the large value of Cohen's d (0.5778 > 0.30 )
Step-by-step explanation:
From the question we are told that
The sample size is n=16
The sample mean is 
The standard deviation is 
The population mean is 
The level of significance is 
The null hypothesis is 
The alternative hypothesis is
Generally the test statistics is mathematically represented as

=> 
=> 
Generally the p-value is mathematically represented as


From the z-table

=> 
=> 
From the obtained values we see that 
Decision Rule
Reject the null hypothesis
Conclusion
There is sufficient evidence to conclude that the supplement has a significant effect on the cognitive skill of elderly adults
Generally the Cohen's d for this study is mathematically represented as

=> 
=> 
G(4)=7(4)+4
G(4)=28+4
G=32
F(32)= 3(32)^2
F= 9216
f(g(4))= 9216
Answer: a. 0.61
b. 0.37
c. 0.63
Step-by-step explanation:
From the question,
P(A) = 0.39 and P(B) = 0.24
P(success) + P( failure) = 1
A) What is the probability that the component does not fail the test?
Since A is the event that the component fails a particular test, the probability that the component does not fail the test will be P(success). This will be:
= 1 - P(A)
= 1 - 0.39
= 0.61
B) What is the probability that a component works perfectly well (i.e., neither displays strain nor fails the test)?
This will be the probability that the component does not fail the test minus the event that the component displays strain but does not actually fail. This will be:
= [1 - P(A)] - P(B)
= 0.61 - 0.24
= 0.37
C) What is the probability that the component either fails or shows strain in the test?
This will simply be:
= 1 - P(probability that a component works perfectly well)
= 1 - 0.37
= 0.63