Answer:
q = (4 - 5 m)/(2 - m)
Step-by-step explanation:
Solve for q:
m = (2 q - 4)/(q - 5)
Hint: | Reverse the equality in m = (2 q - 4)/(q - 5) in order to isolate q to the left hand side.
m = (2 q - 4)/(q - 5) is equivalent to (2 q - 4)/(q - 5) = m:
(2 q - 4)/(q - 5) = m
Hint: | Multiply both sides by a polynomial with respect to q to clear fractions.
Multiply both sides by q - 5:
2 q - 4 = m (q - 5)
Hint: | Write the linear polynomial on the right hand side in standard form.
Expand out terms of the right hand side:
2 q - 4 = m q - 5 m
Hint: | Isolate q to the left hand side.
Subtract m q - 4 from both sides:
q (2 - m) = 4 - 5 m
Hint: | Solve for q.
Divide both sides by 2 - m:
Answer: q = (4 - 5 m)/(2 - m)
Answer:
2/3
Step-by-step explanation:
Hope it helps you ......
Answer: x = -2
Step-by-step explanation:
Answer:
601/100
Step-by-step explanation:
Answer:
Explained below.
Step-by-step explanation:
According to the Central limit theorem, if from an unknown population large samples of sizes n > 30, are selected and the sample proportion for each sample is computed then the sampling distribution of sample proportion follows a Normal distribution.
The mean of this sampling distribution of sample proportion is:
The standard deviation of this sampling distribution of sample proportion is:
A random sample of <em>n</em> = 658 items is sampled randomly from this population.
As the sample size is large, i.e. <em>n</em> = 658 > 30, the Central limit theorem can be applied to approximate the sampling distribution of sample proportion by a Normal distribution.
Compute the mean and standard deviation as follows:
(a)
Compute the probability that the sample proportion is greater than 0.63 as follows:
(b)
Compute the probability that the sample proportion is between 0.60 and 0.66 as follows:
(c)
Compute the probability that the sample proportion is greater than 0.592 as follows:
(d)
Compute the probability that the sample proportion is between 0.57 and 0.60 as follows:
(e)
Compute the probability that the sample proportion is less than 0.51 as follows: