Answer:
99.72% probability that the proportion of Grammy award winners will differ from the singers proportion by less than 5%.
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal probability distribution
When the distribution is normal, we use the z-score formula.
In a set with mean and standard deviation , the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean and standard deviation .
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean and standard deviation
In this question:
So
What is the probability that the proportion of Grammy award winners will differ from the singers proportion by less than 5%?
This is the pvalue of Z when X = 0.41 + 0.05 = 0.46 subtracted by the pvalue of Z when X = 0.41 - 0.05 = 0.36. So
X = 0.46
By the Central Limit Theorem
has a pvalue of 0.9986
X = 0.36
has a pvalue of 0.0014
0.9986 - 0.0014 = 0.9972
99.72% probability that the proportion of Grammy award winners will differ from the singers proportion by less than 5%.
Answer:
Step-by-step explanation:
we have the ratio
To write as percent, multiply the ratio by 100
so
Answer:
And using a calculator, excel or the normal standard table we have that:
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Solution to the problem
Let X the random variable that represent the weights of a population, and for this case we know the distribution for X is given by:
Where and
They select a sample size of n=9 people.The distribution for the sample mean is given by:
And we want to find this probability:
In order to the helicopter can safely lift off. We can use the z score formula given by:
And using a calculator, excel or the normal standard table we have that:
Answer:
9x9+6 could be possible
Step-by-step explanation:
Hope this is what you were looking for, have a great day (;
Answer:
7.5
Step-by-step explanation:
60% = 0.6
18 / 0.6 = 30 (given number)
25% = 0.25
30 * 0.25 = 7.5
Best of Luck!
Answer:
2.7
Step-by-step explanation:
60/100x = 18
x = 10.8
25/100x = ?
25/100 (10.8) = 2.7
hx = 5x + 2
Write the expressions for (g - h)(x) and (g * h)(x) and evaluate (g + h)(−2).
Answer:
Step-by-step explanation:
Given the functions g(x) = x − 3x and h(x) = 5x + 2, we are to calculatae for the expression;
a) (g - h)(x) an (g * h)(x)
(g - h)(x) = g(x) - h(x)
(g - h)(x) = x − 3x -(5x+2)
(g-h)(x) = x-3x-5x-2
(g-h)(x) =-7x-2
b) (g * h)(x) = g(x) * h(x)
(g * h)(x) = (x − 3x)(5x+2)
(g * h)(x) = 5x²+2x-15x²-6x
(g * h)(x) = 5x²-15x²+2x-6x
(g * h)(x) = -10x²-4x
c) To get (g + h)(−2), we need to first calculate (g + h)(x) as shown;
(g + h)(x) an (g * h)(x)
(g + h)(x) = g(x) +h(x)
(g + h)(x) = x − 3x + (5x+2)
(g+h)(x) = x-3x+5x+2
(g+h)(x) =3x+2
Substituting x = -2 into the resulting function;
(g+h)(-2) = 3(-2)+2
(g+h)(-2) = -6+2
(g+h)(-2) = -4
Answer:
Bottom left
Step-by-step explanation:
Function: each x only has one y, and this is the only graph that fits the description