Consider a binomial experiment with n = 20 and p = 0 a. Compute f(12) (to 4 decimals). b. Compute f(16) (to 4 decimals). c. Compute P(x > 16) (to 4 decimals).

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…

In a certain state the proportion of families living below the poverty level is 21 %. For samples of n = 750 randomly selected families, what is the probability that the sample proportion of families that live below the poverty level is within ±0.03 from the population proportion? z=  (p-π)/√(π(1-π)/n) I got an answer of 0.9566. I am not sure if it's right. Can the problem be worked out so I can better understand it?

Consider a binomial experiment with n = 14 and p = 0.5. a. Compute f(0) (to 4 decimals). f(0) = b. Compute f(3) (to 4 decimals). f(3) = %3D c. Compute P(r 4) = e. Compute E(x) (to 1 decimal). E(r) = f. Compute Var(z) and o. Var(x) = (to 2 decimals) (to 2 decimals)