shavon60120 asked:
The management of White Industries is considering a new method of assembling its golf cart. The present method requires 42.3 minutes. On the average, to assemble a cart. The mean assembly time for a random sample of 24 carts using the new method. Was 40.6 minutes and the standard deviation of the sample was 2.7 minutes. Using the .10 level of significance, can we conclude that the assembly time using the new method is faster?
The management of White Industries is considering a new method of assembling its golf cart. The present method requires 42.3 minutes. On the average, to assemble a cart. The mean assembly time for a random sample of 24 carts using the new method. Was 40.6 minutes and the standard deviation of the sample was 2.7 minutes. Using the .10 level of significance, can we conclude that the assembly time using the new method is faster?
1 response so far ↓
1 koolkat // Jan 25, 2009 at 3:00 pm
Don’t know what the answer is, but here’s the process:
(1) H0: mu = 42.3 H1: mu < 42.3
(2) Check conditions - we must know that the distribution of assembly times is normally distributed.
(3) Calculat test statistic (t0 in this case cuz we don’t know sigma): t0 = 40.6 - 42.3 / (2.7 / sqrt(24))
(4) Now use the t-distribution to find the P-value: Probability that we would get a t-score of t0 ASSUMING that the mu is actually 42.3 (H0 is true).
(5) Reject H0 only if P-value is less than alpha (.10 in this case).
You must log in to post a comment.