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