91影视

The sample data is given into the paper

Let鈥檚 take the random sample of length \(120\0.

Draw a normal probability plot using function 鈥渘ormplot鈥� in MATLAB.

Program:

Query:

• Then generate the normal probability plot.

Let鈥檚 take the random sample of length \(120\).

Then calculate the residual using relation

\(residual = data -fit\)

Then, draw a normal probability plot using function 鈥渘ormplot鈥� in MATLAB.

Program:

Query:

• Then generate the normal probability plot of the residuals.

Calculate the SST, SSTR and SSE using given relation

\(SST=\sum x^{2}-\frac{(\sum x)^{2}}{n}\)

\(SST=474-\frac{(80)^{2}}{16}=7.4\)

\(SSTR=\frac{\sum (x_{i})^{2}}{n_{i}}-\frac{\sum (x)^{2}}{n}\)

\(SSTR=\frac{12^{2}}{3}+\frac{25^{2}}{5}+\frac{15^{2}}{5}+\frac{18^{2}}{3} -\frac{(80)^{2}}{16}=46\)

\(SSE=SST-SSTR=28\)

Then,

\(df_{T}=k-1=3-1=2\)

\(df_{E}=n-k=10-3=7\)

\(MSTR=\frac{SSTR}{df_{T}}=\frac{24}{2}=12\)

\(MSE=\frac{SSE}{df_{E}}=\frac{16}{7}=2.2857\)

\(F=\frac{MSTR}{MSE}=\frac{12}{2.2857}\approx 5.25\)

After calculating these values put all into the table and get ANOVA table

The \(p-\)value is the probability value which obtaining by the test statistics, or a value more extreme. The \(P-\)value is the number in the row title of the \(F-\)distribution table which containing \(F-\)value in the row \(dfd=df_{E}=7\) and in the column \(dfn=df_{T}=2\)

So, the \(p-\)value lie between

\(0.025<P<0.050\)

And if the \(p-\)value is less than significance level then it will reject the null hypothesis.

\(P<0.05\Rightarrow\) Reject \(H_{0}\)