function StatsPractice
% Coded by Nigel Reuel on 9.5.2017
% This script shows basic stat functions with Matlab
%
% First step import data
[num, txt, ~] = xlsread('ClassData.xlsx');
m = 10;
% One example of univariate data = time it takes to commute
Time = num(:,1);
AvgTime = mean(Time)
MedianTime = median(Time)
TimewOutlier = [Time; 300];
AvgTime2 = mean(TimewOutlier)
MedianTime2 = median(TimewOutlier)
% Use measures of spread
StdevTime = std(Time)
IQRtime = iqr(Time)
% Demo the boxplot
boxplot(Time)
% Let's show boxplots that are grouped
boxplot(Time,txt)
% Another way to look at univariate data is the histogram
hist(Time)
ylabel('Frequency')
xlabel('Time (min)')
% If you want to specify the bins 
% Way 1 - number of bins
nbins = 5;
hist(Time,nbins)
ylabel('Frequency')
xlabel('Time (min)')
% Way 2 - specify bin centers
binctr = [0:2:30];
hist(Time,binctr)
% You can report out the heights of the bars (counts)
count = hist(Time,binctr)
% Now let's practice distributions and how to use them
% Data for time to failure of an electronic piece
life = [ 6.2 16.1 16.3 19.0 12.2  8.1  8.8  5.9  7.3  8.2 ...
        16.1 12.8  9.8 11.3  5.1 10.8  6.7  1.2  8.3  2.3 ...
         4.3  2.9 14.8  4.6  3.1 13.6 14.5  5.2  5.7  6.5 ...
         5.3  6.4  3.5 11.4  9.3 12.4 18.3 15.9  4.0 10.4 ...
         8.7  3.0 12.1  3.9  6.5  3.4  8.5  0.9  9.9  7.9];
% First pass we will not define the bins
hist(life)
ylabel('Frequency')
xlabel('Time (min)')
% Next let's set our bins
binwidth = 2;
binctrs = [1:binwidth:19];
counts = hist(life,binctrs)
xlabel('Time to Failure')
ylabel('Frequency')
% Now let's fit the data to a Weibull Distribution
paramEst = wblfit(life)
% So now we have the parameters for the Weibull Dist (a,b)
% To plot the fit distribution, we need to normalize the y axis 
n = length(life);
prob = counts/(n*binwidth);
bar(binctrs,prob)
X = linspace(0,20,100);
Y = wblpdf(X,paramEst(1),paramEst(2));
hold on
plot(X,Y,'r')
% Let's say your boss wants you to simulate the process, 
% You can use the model to simulate random outputs
OneMeasurment = wblrnd(paramEst(1),paramEst(2))



end