Answer:
Approximately 68%.
Step-by-step explanation:
The Empirical Rule states that, for a normally distributed random variable:
Approximately 68% of the measures are within 1 standard deviation of the mean.
Approximately 95% of the measures are within 2 standard deviations of the mean.
Approximately 99.7% of the measures are within 3 standard deviations of the mean.
In this problem, we have that:
Mean = 1, standard deviation = 0.05.
Estimate the percent of pails with volumes between 0.95 gallons and 1.05 gallons.
0.95 = 1 - 0.05
1.05 = 1 + 0.05
So within 1 standard deviation of the mean, which by the Empirical Rule, is approximately 68% of values.
The estimate of the population proportion of defectives is 0.05.
Given that,
There are 10 different samples of 50 observations, that is, total of 500 observations.
To find : The estimate of the population proportion of defectives
And total number of defectives from 500 observations is (5+1+1+2+3+3+1+4+2+3) = 25
Thus, the point estimate for the population proportion defectives will be,
=25/500=0.05
or just obtain the individual proportion of each sample and then take their average to obtain the same result.
Thus, the point estimate for the population proportion defectives will be 0.05
To learn more about proportion click here:
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In this case u can’t use the distributive property. U just multiple whats in the parenthesis (39•5)=195 and that’s ur answer.
Let’s say if the problem said 5(2+1) u can’t use the distributive property bc u have to do what’s in the parentheses first. 5(3)=15
But If u had a problem like 2(4x+6) then u can use the distributive property. This is bc u can’t add 4x+6 bc they aren’t like terms. So u multiple the 2 by 4x which is 8x and the 2 by 6 which is 12 then ur answer would be : 8x+12
Answer:
5/8 : 1/4 :: m : 1 proportion
5/8 = m/4 product means/extremes
5/2 = m
Step-by-step explanation:
as the function is polynomial domain exist for all real number ie (-infinity to + infinity) but range exist (0 to +infinity ) due to modulus negetive range do not exist
