<span>1.Take a measurement in feet.
</span>2.Multiply or divide your measurement by a conversion factor.<span>
</span>
We need to find out how many adults must the brand manager survey in order to be 90% confident that his estimate is within five percentage points of the true population percentage.
From the given data we know that our confidence level is 90%. From Standard Normal Table we know that the critical level at 90% confidence level is 1.645. In other words,
.
We also know that E=5% or E=0.05
Also, since,
is not given, we will assume that
=0.5. This is because, the formula that we use will have
in the expression and that will be maximum only when
=0.5. (For any other value of
, we will get a value less than 0.25. For example if,
is 0.4, then
and thus,
.).
We will now use the formula

We will now substitute all the data that we have and we will get



which can approximated to n=271.
So, the brand manager needs a sample size of 271
Answer:
at the begining
Step-by-step explanation:
Answer:

And on this case if we see the significance level given
we see that
so we fail to reject the null hypothesis that the observed outcomes agree with the expected frequencies at 10% of significance.
Step-by-step explanation:
A chi-square goodness of fit test determines if a sample data obtained fit to a specified population.
represent the p value for the test
O= obserbed values
E= expected values
The system of hypothesis for this case are:
Null hypothesis: ![O_i = E_i[/tex[Alternative hypothesis: [tex]O_i \neq E_i](https://tex.z-dn.net/?f=O_i%20%3D%20E_i%5B%2Ftex%5B%3C%2Fp%3E%3Cp%3EAlternative%20hypothesis%3A%20%5Btex%5DO_i%20%5Cneq%20E_i%20)
The statistic to check the hypothesis is given by:

On this case after calculate the statistic they got: 
And in order to calculate the p value we need to find first the degrees of freedom given by:
, where k represent the number of levels (on this cas we have 10 categories)
And in order to calculate the p value we need to calculate the following probability:

And on this case if we see the significance level given
we see that
so we fail to reject the null hypothesis that the observed outcomes agree with the expected frequencies at 10% of significance.