Jacob Lee is a frequent traveler between Los Angeles and San Diego. For the past month, he wrote down the flight times in minutes on three different airlines. The results are:

Goust Jet Red Cloudtran
51 50 52
51 53 55
52 52 60
42 62 64
51 53 61
57 49 49
47 50 49
47 49
50 58
60 54
54 51
49 49
48 49
48 50

Required:
a. Use the α =0.05 significance level and the six-step hypothesis-testing process to check if there is a difference in the mean flight times among the three airlines.
b. Develop a 95% confidence interval for the difference in the means between Goust and Cloudtran

Respuesta :

Solution :

We know that

[tex]$H_0: \mu_1 = \mu_2=\mu_3$[/tex]

[tex]$H_1 :$[/tex] At least one mean is different form the others (claim)

We need to find the critical values.

We know k = 3 , N = 35, α = 0.05

d.f.N = k - 1

       = 3 - 1 = 2

d.f.D = N - k

        = 35 - 3 = 32

SO the critical value is 3.295

The mean and the variance of each sample :

Goust                      Jet red                 Cloudtran

[tex]$\overline X_1 =50.5$[/tex]           [tex]$\overline X_2 =50.07143$[/tex]        [tex]$\overline X_3 =55.71429$[/tex]

[tex]$s_1^2=19.96154$[/tex]      [tex]$s_2^2=14.68681$[/tex]         [tex]$s_3^2=36.57143$[/tex]

The grand mean or the overall mean is(GM) :

[tex]$\overline X_{GM}=\frac{\sum \overline X}{N}$[/tex]

         [tex]$=\frac{51+51+...+49+49}{35}$[/tex]

        = 52.1714

The variance between the groups

[tex]$s_B^2=\frac{\sum n_i\left( \overline X_i - \overline X_{GM}\right)^2}{k-1}$[/tex]

     [tex]$=\frac{\left[14(50.5-52.1714)^2+14(52.07143-52.1714)^2+7(55.71426-52.1714)^2\right]}{3-1}$[/tex]

   [tex]$=\frac{127.1143}{2}$[/tex]

   = 63.55714

The Variance within the groups

[tex]$s_W^2=\frac{\sum(n_i-1)s_i^2}{\sum(n_i-1)}$[/tex]

    [tex]$=\frac{(14-1)19.96154+(14-1)14.68681+(7-1)36.57143}{(14-1)+(14-1)+(7-1)}$[/tex]

   [tex]$=\frac{669.8571}{32}$[/tex]

  = 20.93304

The F-test  statistics value is :

[tex]$F=\frac{s_B^2}{s_W^2}$[/tex]

  [tex]$=\frac{63.55714}{20.93304}$[/tex]

  = 3.036212

Now since the 3.036 < 3.295, we do not reject the null hypothesis.

So there is no sufficient evidence to support the claim that there is a difference among the means.

The ANOVA table is :

Source       Sum of squares    d.f    Mean square    F

Between    127.1143                 2      63.55714          3.036212

Within        669.8571             32      20.93304

Total           796.9714            34

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