Answer:
4 - i
Step-by-step explanation:
Intuitively, the answer will be 4 - i, as the other numbers are too big to have a square as small as 17i. Also, we know that i will not be in the end result, which means that we should have a negative in the result as well.
To test this, we can simply treat 4 and -i as the sides of a right triangle and find the hypotenuse:
So indeed the answer is 4 - i
Answer:
So with the p value obtained and using the significance level given we have
so we can conclude that we don't have enough evidence to reject the null hypothesis, and we can said that at 1% of significance the population proportion of extroverts among college student government leaders is not different from 0.82.
Step-by-step explanation:
1) Data given and notation
n=74 represent the random sample taken
X=57 represent the number of people found extroverts
estimated proportion of people found extroverts.
is the value that we want to test
represent the significance level
Confidence=99% or 0.959
z would represent the statistic (variable of interest)
represent the p value (variable of interest)
2) Concepts and formulas to use
We need to conduct a hypothesis in order to test if population proportion of extroverts among college student government leaders is different (either way) from 82%, the system of hypothesis would be on this case:
Null hypothesis:
Alternative hypothesis:
When we conduct a proportion test we need to use the z statisitc, and the is given by:
(1)
The One-Sample Proportion Test is used to assess whether a population proportion is significantly different from a hypothesized value
.
3) Calculate the statistic
Since we have all the info requires we can replace in formula (1) like this:
4) Statistical decision
It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.
The significance level provided . The next step would be calculate the p value for this test.
Since is a bilateral test the p value would be:
So with the p value obtained and using the significance level given we have
so we can conclude that we don't have enough evidence to reject the null hypothesis, and we can said that at 1% of significance the population proportion of extroverts among college student government leaders is not different from 0.82.