Expand logarithms equation
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The measure of center best represents the data set is Mean or Median.
Given
Data Set Best Measure of Center {27, 29, 26, 28, 25}.
<h3>What is the mean of the data set? </h3>The mean is the average of a set of data.
The mean is found by finding the sum of the data and then dividing the sum by the number of data.
<h3 />The mean of the given data set is;
Arranging the data set in the ascending order
{25, 26, 27, 28, 29}
The median is defined as the middle value of the given data set.
The median of the data set is 27.
Hence, the measure of center best represents the data set is Mean or Median.
To know more about mean and median click the link is given below.
Answer:
With outlier (102)
If we compare the p value and a significance level assumed we see that
so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so we can conclude that the true mean is not significantly higher than 125 feet at 5% of significance.
Without outlier (102)
And we conclude that we reject the null hypothesis since . So the final conclusion would be not use the method since the value of 102 observed can be a potential outlier, removing this value we see that we reject the null hypothesis and we have a significant result that the true mean is higher than 125.
Step-by-step explanation:
Previous concepts and data given
The margin of error is the range of values below and above the sample statistic in a confidence interval.
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
Data: 129, 128, 130, 132, 135, 123, 102, 125, 128, 130
We can calculate the mean with the following formulas:
represent the sample mean
represent the sample standard deviation
n=10 represent the sample selected
significance level
State the null and alternative hypotheses.
We need to conduct a hypothesis in order to check if the mean is significantly higher than 125, the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
If we analyze the size for the sample is < 30 and we don't know the population deviation so is better apply a t test to compare the actual mean to the reference value, and the statistic is given by:
(1)
t-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".
Calculate the statistic
We can replace in formula (1) the info given like this:
P-value
First we need to calculate the degrees of freedom given by:
Then since is a right tailed sided test the p value would be:
Conclusion
If we compare the p value and a significance level assumed we see that
so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so we can conclude that the true mean is not significantly higher than 125 feet at 5% of significance.
Using all the data we see that we don;t have enough info to conclude that the true mean is higher than 125, but if we see careful 9 of the 10 values are over the limit of 125 feet. And if we repeat the procedure with the outlier of 102. We got this:
represent the sample mean
represent the sample standard deviation
First we need to calculate the degrees of freedom given by:
Then since is a right tailed sided test the p value would be:
And we conclude that we reject the null hypothesis since . So the final conclusion would be not use the method since the value of 102 observed can be a potential outlier removing this value we see that we reject the null hypothesis and we have a significant result that the true mean is higher than 125.