Question 122475This question is from textbook Statistical Techniques in Business and Economics,  
:  Tests of Hypothesis
 
18) 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? 
 
This question is from textbook Statistical Techniques in Business and Economics,  
 Answer by Edwin McCravy(20064)      (Show Source): 
You can  put this solution on YOUR website! 
Tests of Hypothesis 
18) 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?
Since the sample was 24, which is less than 30, we must use the t-test,
not the z-test:  
H0: u = 42.3
Ha: u < 43.3
This is a left-tail test.
Calculate the test statistic:
     _
     x - u     40.6 - 42.3 
t = ------- = ------------- = -3.084542639
      s/Vn       2.7/V24
Now we look at the t-table, pasted below. Taking the degrees of 
freedom (df) as 1 less than the number in the sample, or 23, and we find 
the entry I have marked in red below in the table, which is 1.319, 
but we consider it to be -1.319.
The test t-statistic -3.084542639 is well into the rejection
region since it is left of -1.319.  
 
So we reject the hypothesis that the mean with the new method has
not significantly reduced the mean from 42.3. So we assume the new
method is faster. 
 
      T Table
 
df -	degrees of freedom for t curve  
P  -	area under the t curve with df degrees of freedom to the right of t(df) 
 
 Example: 
P[t(2) > 2.92] = 0.05 
P[-2.92 < t(2) < 2.92] = 0.9 
 
						Upper tail probability p						 
	0.25	0.2	0.15	0.1	0.05	0.025	0.02	0.01	0.005	0.0025	0.001	0.0005 
  df 
   1	1.000	1.376	1.963	3.078	6.314	12.706	15.895	31.821	63.657 27.321	318.309	636.619 
   2	0.817	1.061	1.386	1.886	2.920	4.303	4.849	6.965	9.925	14.089	22.327	31.599 
   3	0.765	0.979	1.250	1.638	2.353	3.182	3.482	4.541	5.841	7.453	10.215	12.924 
   4	0.741	0.941	1.190	1.533	2.132	2.776	2.999	3.747	4.604	5.598	7.173	8.610 
   5	0.727	0.920	1.156	1.476	2.015	2.571	2.757	3.365	4.032	4.773	5.893	6.869 
   6	0.718	0.906	1.134	1.440	1.943	2.447	2.612	3.143	3.707	4.317	5.208	5.959 
   7	0.711	0.896	1.119	1.415	1.895	2.365	2.517	2.998	3.499	4.029	4.785	5.408 
   8	0.706	0.889	1.108	1.397	1.860	2.306	2.449	2.896	3.355	3.833	4.501	5.041 
   9	0.703	0.883	1.100	1.383	1.833	2.262	2.398	2.821	3.250	3.690	4.297	4.781 
  10	0.700	0.879	1.093	1.372	1.812	2.228	2.359	2.764	3.169	3.581	4.144	4.587 
  11	0.697	0.876	1.088	1.363	1.796	2.201	2.328	2.718	3.106	3.497	4.025	4.437 
  12	0.696	0.873	1.083	1.356	1.782	2.179	2.303	2.681	3.055	3.428	3.930	4.318 
  13	0.694	0.870	1.079	1.350	1.771	2.160	2.282	2.650	3.012	3.372	3.852	4.221 
  14	0.692	0.868	1.076	1.345	1.761	2.145	2.264	2.624	2.977	3.326	3.787	4.140 
  15	0.691	0.866	1.074	1.341	1.753	2.131	2.249	2.602	2.947	3.286	3.733	4.073 
  16	0.690	0.865	1.071	1.337	1.746	2.120	2.235	2.583	2.921	3.252	3.686	4.015 
  17	0.689	0.863	1.069	1.333	1.740	2.110	2.224	2.567	2.898	3.222	3.646	3.965 
  18	0.688	0.862	1.067	1.330	1.734	2.101	2.214	2.552	2.878	3.197	3.610	3.922 
  19	0.688	0.861	1.066	1.328	1.729	2.093	2.205	2.539	2.861	3.174	3.579	3.883 
  20	0.687	0.860	1.064	1.325	1.725	2.086	2.197	2.528	2.845	3.153	3.552	3.850 
  21	0.686	0.859	1.063	1.323	1.721	2.080	2.189	2.518	2.831	3.135	3.527	3.819 
  22	0.686	0.858	1.061	1.321	1.717	2.074	2.183	2.508	2.819	3.119	3.505	3.792 
  23	0.685	0.858	1.060	1.319	1.714	2.069	2.177	2.500	2.807	3.104	3.485	3.768 
  24	0.685	0.857	1.059	1.318	1.711	2.064	2.172	2.492	2.797	3.091	3.467	3.745 
  25	0.684	0.856	1.058	1.316	1.708	2.060	2.167	2.485	2.787	3.078	3.450	3.725 
  26	0.684	0.856	1.058	1.315	1.706	2.056	2.162	2.479	2.779	3.067	3.435	3.707 
  27	0.684	0.855	1.057	1.314	1.703	2.052	2.158	2.473	2.771	3.057	3.421	3.690 
  28	0.683	0.855	1.056	1.313	1.701	2.048	2.154	2.467	2.763	3.047	3.408	3.674 
  29	0.683	0.854	1.055	1.311	1.699	2.045	2.150	2.462	2.756	3.038	3.396	3.659 
  30	0.683	0.854	1.055	1.310	1.697	2.042	2.147	2.457	2.750	3.030	3.385	3.646 
  40	0.681	0.851	1.050	1.303	1.684	2.021	2.123	2.423	2.704	2.971	3.307	3.551 
  50	0.679	0.849	1.047	1.299	1.676	2.009	2.109	2.403	2.678	2.937	3.261	3.496 
  60	0.679	0.848	1.045	1.296	1.671	2.000	2.099	2.390	2.660	2.915	3.232	3.460 
  80	0.678	0.846	1.043	1.292	1.664	1.990	2.088	2.374	2.639	2.887	3.195	3.416 
 100	0.677	0.845	1.042	1.290	1.660	1.984	2.081	2.364	2.626	2.871	3.174	3.390 
1000	0.675	0.842	1.037	1.282	1.646	1.962	2.056	2.330	2.581	2.813	3.098	3.300 
z*	0.674	0.841	1.036	1.282	1.645	1.960	2.054	2.326	2.576	2.807	3.090	3.291
 
 
	50%	60%	70%	80%	90%	95%	96%	98%	99%	99.5%	99.8%	99.9% 
						Confidence level C 
Edwin 
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