Question #129863
The life of a 60- watt light bulb in hours is known to be normally distributed with σ = 25
hours. Create 5 different random samples of 100 bulbs each which has a mean life of x_bar ~
1000 hours and perform one-way ANOVA with state it.
1
Expert's answer
2020-08-19T17:55:09-0400

The total sample size is N=500.N=500. Therefore, the total degrees of freedom are:


dftotal=5001=499df_{total}=500-1=499

The between-groups degrees of freedom are dfbetween=51=4,df_{between}=5-1=4, and the within-groups degrees of freedom are:


dfwithin=dftotaldfbetween=4994=495df_{within}=df_{total}-df_{between}=499-4=495

Sum=9964599684996879969999592Average=996.45996.84996.87996.99995.92\begin{matrix} Sum= & 99645 & 99684 & 99687 & 99699 & 99592 \\ Average= & 996.45 & 996.84 & 996.87 & 996.99 & 995.92 \end{matrix}


iXij2=9931335599390488993971479942047199420471\begin{matrix} \displaystyle\sum_{i}X_{ij}^2= \\ 99313355 & 99390488 & 99397147 & 99420471 & 99420471 \end{matrix}


St.Dev.=14.93914.73314.96414.75910.249\begin{matrix} \displaystyle St.Dev.= \\ 14.939 & 14.733 & 14.964 & 14.759 & 10.249 \end{matrix}


SSi=(ni1)si2SS_i=(n_i-1)s_i^2

(1001)14.9392=22094.75(100-1)14.939^2=22094.75

(1001)14.7332=21489.44(100-1)14.733^2=21489.44

(1001)14.9642=22167.31(100-1)14.964^2=22167.31

(1001)14.7592=21564.99(100-1)14.759^2=21564.99

(1001)10.2492=10399.36(100-1)10.249^2=10399.36


SS=22094.7521489.4422167.3121564.9910399.36\begin{matrix} \displaystyle SS= \\ 22094.75 & 21489.44 & 22167.31 & 21564.99 & 10399.36 \end{matrix}


n=100100100100100\begin{matrix} n= & 100 & 100 & 100 & 100 & 100 \\ \end{matrix}


i,jXij=\displaystyle\sum_{i,j}X_{ij}=

=99645+99684+99687+99699+99592==99645 +99684 + 99687 + 99699 + 99592=

=498307=498307


i,jXij2=\displaystyle\sum_{i,j}X_{ij}^2=

=99313355+99390488+99397147+99420471+99420471==99313355+ 99390488 + 99397147+99420471 + 99420471=

=496717525=496717525


SStotal=i,jXij21N(i,jXij)2=97792.502SS_{total}=\displaystyle\sum_{i,j}X_{ij}^2-\dfrac{1}{N}(\displaystyle\sum_{i,j}X_{ij})^2=97792.502

SSwithin=22094.75+21489.44+22167.31+SS_{within}=22094.75 + 21489.44 +22167.31++21564.99+10399.36=97715.85+21564.99+ 10399.36=97715.85

SSbetween=jnj(xˉjxˉˉ)2=76.652SS_{between}=\displaystyle\sum_{j}n_j(\bar{x}_j-\bar{\bar{x}})^2=76.652MSbetween=SSbetweendfbetween=76.6524=19.163MS_{between}=\dfrac{SS_{between}}{df_{between}}=\dfrac{76.652}{4}=19.163MSwithin=SSwithindfwithin=97715.85495=197.406MS_{within}=\dfrac{SS_{within}}{df_{within}}=\dfrac{97715.85}{495}=197.406F=MSbetweenMSwithin=19.163197.406=0.097F=\dfrac{MS_{between}}{MS_{within}}=\dfrac{19.163}{197.406}=0.097

The following null and alternative hypotheses need to be tested:

H0:μ1=μ2=μ3=μ4=μ5H_0: \mu_1=\mu_2=\mu_3=\mu_4=\mu_5

H1:H_1: Not all means are equal.

The above hypotheses will be tested using an F-ratio for a One-Way ANOVA.


Based on the information provided, the significance level is α=0.05,\alpha=0.05, and the degrees of freedom are df1=4df_1=4 and df2=4,df_2=4, therefore, the rejection region for this F-test is R={F:F>Fc=2.39}.R=\{F:F>F_c=2.39\}.

Test Statistics


F=MSbetweenMSwithin=19.163197.406=0.097F=\dfrac{MS_{between}}{MS_{within}}=\dfrac{19.163}{197.406}=0.097



Since it is observed that F=0.097<2.39=Fc,F=0.097<2.39=F_c, it is then concluded that the null hypothesis is not rejected. Therefore, there is not enough evidence to claim that not all 5 population means are equal, at the α=0.05\alpha=0.05 significance level.


Using the P-value approach: The p-value is p=0.9834,p=0.9834, and since  p=0.98340.05,p=0.9834\geq0.05, it is concluded that the null hypothesis is not rejected. Therefore, there is not enough evidence to claim that not all 5 population means are equal, at the α=0.05\alpha=0.05 significance level.



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