Answer:
The probability that the sample proportion is between 0.35 and 0.5 is 0.7895
Step-by-step explanation:
To calculate the probability that the sample proportion is between 0.35 and 0.5 we need to know the z-scores of the sample proportions 0.35 and 0.5.
z-score of the sample proportion is calculated as
z=
where
- p(s) is the sample proportion of first time customers
- p is the proportion of first time customers based on historical data
For the sample proportion 0.35:
z(0.35)=
≈ -1.035
For the sample proportion 0.5:
z(0.5)=
≈ 1.553
The probabilities for z of being smaller than these z-scores are:
P(z<z(0.35))= 0.1503
P(z<z(0.5))= 0.9398
Then the probability that the sample proportion is between 0.35 and 0.5 is
P(z(0.35)<z<z(0.5))= 0.9398 - 0.1503 =0.7895
Answer:
6
Step-by-step explanation:
4(6) - 7y = -18
24 - 7y = -18
-7y= -42
y= 6
Answer:
3/32
Step-by-step explanation:
One approach to doing this probelm is to evaluate all three functions F, G and H at x = 2:
F(2) = 2(2) - 1 = 3
G(2) = 3(2) + 2 = 8
H(2) = (2)^2 = 4
3/8
Then (F/G)(2) = (3/8), and (F/G/H) = -------- = 3/32
4
Answer:

Step-by-step explanation:
Exponents are basically just saying how many times the number is multiplied by itself.
In the expression
, we can see that 10 is being multiplied by itself 5 times.
So the exponent becomes 5, and the base is 10.
.
Hope this helped!
Answer:
a) Statistic.
b) The population proportion is expected to be between 0.29 and 0.31 with a 94% degree of confidence.
Step-by-step explanation:
a) The proportion of 30% is a statistic, as it is a value that summarizes data only from the sample taken in the study from USA Today. Other samples may yield different proportions.
b) We can use the statistic to estimate a confidence interval for the parameter of the population.
The standard error for the proportion is calculated as:

The margin of error is 0.01. We can use this value to determine the level of confidence that represents.
The formula for the margin of error is:

This z-value, according to the the standard normal distribution, corresponds to a confidence interval of 94%.
The interval for this margin of error is:

Then, we can conclude that the population proportion is expected to be between 0.29 and 0.31 with a 94% degree of confidence.