N(100,5)N(115,15)

Then run the simulation 1,000 times and compute how many times the null hypothesis was rejected the end of 1,000 times because that each sample sizes scanning native 2 to 50.

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Finally, I need to plot the result of the rejections of H0 versus the sample size.

h = zeros(1000,1);k = 0;for i = 1:1000 r1 = (); r2 = (); because that j= 2:50 r1(j-1)=normrnd(100,5,<1,j>); r2(j-1)=normrnd(110,15,<1,j>); end h(i)=ttest2(r1,r2) if h(i)==1 k=k+1; finish percent_of_rejection_Null=(k/1000*100);end%plot(h vs sample_size)Could somebody help me to exactly the above code?

There to be a few issues through your code:

ri is a vector of changing size therefore you should append it to a struct that deserve to store elements with different sizes -> cell array.percent_of_rejection_Null demands to be a vector to keep all the values.you didn"t point out what form of plot girlfriend are looking for specifically, I proved the bar plot but it"s simple to readjust to the preferred one friend need.the calculation of h was problematic, its a vector that 50 every iteration therefore need to calculate the sum of 1.

The item of code is:

h = zeros(1000,1);percent_of_rejection_Null = zeros(1000,1);k = 0;for i = 1:1000 r1 = ; r2 = ; for j= 2:50 r1j-1=normrnd(100,5,<1,j>); r2j-1=normrnd(110,15,<1,j>); finish h = cellfun(
ttest2, r1, r2); k = sum(h==1); percent_of_rejection_Null(i) = (k/1000*100);endfigure;plot(percent_of_rejection_Null)The result plot is:

If the output isn"t what you to be after, please modify your question in order for me to adjust.

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