HELP! Which shapes are decomposed correctly so that it could be used to to find its area? Assume side lengths are known.
2 answers:
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Answer:
Comparing the p value with the significance level given we see that
so we can conclude that we reject the null hypothesis, and a would be a significant difference in the true mean lifetime expectancy number between rural and urban living.
Step by step explanation:
Data given and notation
represent the mean for rural
represent the mean for urban
represent the sample standard deviation for rural
represent the sample standard deviation for urban
sample size for the group rural
sample size for the group urban
t would represent the statistic (variable of interest)
significance level provided
Develop the null and alternative hypotheses for this study?
We need to conduct a hypothesis in order to check if the means for the two groups are different, the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
Since we don't know the population deviations for each group, for this case is better apply a t test to compare means, 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 whether the means of two groups are equal to each other.
Determine the critical value(s).
Based on the significance level and
we can find the critical values from the t distribution dith degrees of freedom df=n1+n2-2=55+88-2=141, we are looking for values that accumulates 0.01 of the area on each tail on the t distribution.
For this case the two values are and
Calculate the value of the test statistic for this hypothesis testing.
Since we have all the values we can replace in formula (1) like this:
What is the p-value for this hypothesis test?
Since is a bilateral test the p value would be:
Based on the p-value, what is your conclusion?
Comparing the p value with the significance level given we see that
so we can conclude that we reject the null hypothesis, and a would be a significant difference in the true mean lifetime expectancy number between rural and urban living.