Let x1, X2, ..., Xn be a random sample from a geometric distribution. We wish to find the maximum likelihood estimator for p. What is the likelihood function of p? For the instructor, this was question 6. X x-bar X 1/x-bar X (1-p)×-1p X (1-p)(Ex)-1p X (1-p)2x)-1p" (1-p)(Zx)-pn X (1-p)(x-bar)-npn

We want to test whether or not more students are absent on Friday afternoon classes than on Wednesday afternoon classes. In a random sample of 300 students with Friday afternoon classes, 62 missed the class. In a different random sample of 300 students with Wednesday afternoon classes, 22 missed the class. The table below summarizes this information. The standard error (SE) is given to save calculation time if you are not using software. Class Day total # of absences (x) total # of students (n) Friday Wednesday (b) Find the critical value. (c) Find the p-value. Test the claim that the absentee rate on all Friday afternoon classes is greater than the absentee rate on all Wednesday afternoon classes. Test this claim at the 0.05 significance level. (a) Find the test statistic. O No 62 22 Standard Error: SE= 0.0283313724811677 (d) Is there sufficient data to support the claim? Yes 300 300 proportion = x/n 0.206666666666667 0.0733333333333333 Can you support the claim at the 0.01…

Hello, I really need help with this problem because I don't understand it, can you please do this problem step by step and can you label the parts as well

Please I want a handwritten solution, not printed