Answer this asapppp i just took a ss of it
2 answers:
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Answer:
<em>(A) 560 students</em>
<em>(B) P = 0.41</em>
Step-by-step explanation:
<em>(Please check the attached picture for more details)</em>
As given, a survey of 1000 students found that:
41% of the surveyed students were freshmen
=> 1000 x 41/100 = 410 surveyed students were freshmen
31% were juniors
=> 1000 x 31/100 = 310 surveyed students were junior
67% of surveyed students lived on the college campus
=> 1000 x 67/100 = 670 surveyed students lived on the campus
<em>(A) 260 of the surveyed students were freshmen living on the campus</em>
=> A = 410 - 260 = 150 surveyed students were freshmen NOT living on the campus
=> B = 670 - 260 = 410 surveyed students were not freshmen living on the campus
=> The number of surveyed students who were either freshmen or living on the campus:
N = A + B = 150 + 410 = 560
<em>(B) From a previous survey you know that of interviewed juniors, only 23% live on campus (we don't really need this)</em>
=>The probability a surveyed student is a junior or someone that lives on campus: P = (670 - 260)/1000 = 0.41
I hope this helps!
Answer:
The value of the test statistic is
Step-by-step explanation:
Before finding the test statistic, we need to understand the central limit theorem and subtraction of normal variables.
Central Limit Theorem
The Central Limit Theorem establishes 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.
Subtraction between normal variables:
When two normal variables are subtracted, the mean is the difference of the means, while the standard deviation is the square root of the sum of the variances.
Sample 1:
Sample 2:
The test statistic is:
In which X is the sample mean, is the value tested at the null hypothesis, and s is the standard error.
0 is tested at the null hypothesis:
This means that
Distribution of the difference:
What is the value of the test statistic?
The value of the test statistic is