Answer:
Step-by-step explanation:
Data given and notation
represent the sample mean
represent the sample standard deviation for the sample
sample size
represent the value that we want to test
represent the significance level for the hypothesis test.
t would represent the statistic (variable of interest)
represent the p value for the test (variable of interest)
State the null and alternative hypotheses.
We need to conduct a hypothesis in order to check if the mean weight is less than 4 ounces, 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:
Answer:
10
Step-by-step explanation:
Answer:
A. ![\left[\begin{array}{cc}0.93&0.07&\\0.01&0.99&\end{array}\right]](https://tex.z-dn.net/?f=%5Cleft%5B%5Cbegin%7Barray%7D%7Bcc%7D0.93%260.07%26%5C%5C0.01%260.99%26%5Cend%7Barray%7D%5Cright%5D)
B. (0.85 0.15)
C. 79.2% population in the city while 20.8% population in the suburb
Step-by-step explanation:
(a) The transition matrix for the information is
C S
(b) the probability vector for the information is

and this gives us
(0.85 0.15)
(c) we simply multiply the above two matrices to find the percent of the population can be expected to be in each category after one year after
in the city there are 79.2% while in the suburb, there are 20.8%