Final

Question 1

ep=randn(30,1)*5;

Answer 1

sample a normal distribution with zero mean and prescribed standard deviation/spread

Question 2

x=10+ep;

Answer 2

shift for a prescribed mean

Question 3

ep=randn(30,1)5;
x=10+ep;
figure(1)
dotplot(x,30,0.05,1)
function dotplot(x,nbins,delta,ymax)
[n,edges]=histcounts(x,nbins);
for i=1:length(n)
for j=1:n(i) plot((edges(i)+edges(i+1))/2,jdelta,’ob’,’markersize’,8,’markerfacecolor’,’w’); hold on end
end
set(gca,’YTick’,[]);
ylim([0 ymax])
end

Answer 3

code for dot plot

Question 4

function dotplot(x,nbins,delta,ymax)

Answer 4

dot plot of data in x with nbins, dot spacing delta, and y-axis maximum ymax

Question 5

[n,edges]=histcounts(x,nbins);

Answer 5

prescribe the bins and counts (matlab algorithm)

Question 6

set(gca,’YTick’,[])

Answer 6

hide the y-axis ticks

Question 7

plot(x,’o’,’markersize’,8,’markerfacecolor’,’w’); hold on ylabel(’value’)
xlabel(’sample number’)

Answer 7

scatter and time-series plot

Question 8

boxplot(x)
ylabel(’value’)
xlabel(’sample’)

Answer 8

box plot

Question 9

x=[8 4 1 8 4 7 6 9 8]; n=length(x); x=sort(x)

Answer 9

order the data for inspection.

Question 10

q1=x(round(1/4(n+1))) q2=x(round(2/4(n+1))) q3=x(round(3/4*(n+1))) IQR=(q3-q1)

Answer 10

here, quartiles from rounding, not interpolation. Matlab interpolates

Question 11

min(x(x>q1-1.5IQR)) max(x(x<q3+1.5IQR))

Answer 11

whiskers

Question 12

x((q1-3IQR)<x & x<(q1-1.5IQR))
x((q3+1.5IQR)<x & x<(q3+3IQR))

Answer 12

outliers

Question 13

x(x<(q1-3IQR)
x(x>(q3+3IQR))

Answer 13

extreme outliers

Question 14

histogram(x,10) xlabel(’value’) ylabel(’counts’)

Answer 14

histogram

Question 15

scatterhist(x,y)
xlabel(’x’)
ylabel(’y’)

Answer 15

marginal plot for bivariate data

Question 16

n=length(x)

Answer 16

number of data points

Question 17

xbar=mean(x)

Answer 17

mean of data in x

Question 18

yp=y-mean(y)
xp=x-mean(x)

Answer 18

deviations

Question 19

Syy=sum(y.^2)-nybar^2 % correlations Sxx=sum(x.^2)-nxbar^2 Sxy=sum(x.y)-nxbarybar
r1=Sxy/sqrt(SxxSyy)

Answer 19

gets you correlation and correlation coefficient (r1)

Question 20

f=pdf(’norm’,x,mu,sd)

Answer 20

normal PDF

Question 21

F=cdf(’norm’,x,mu,sd)

Answer 21

normal cumulative PDF

Question 22

P=cdf(’norm’,2,mu,sd)-cdf(’norm’,1,mu,sd)

Answer 22

using cumulative distributions

Question 23

P=integral(@(x)pdf(’norm’,x,mu,sd),1,2)

Answer 23

using numerical integration - gets you same value as P=cdf

Question 24

x=icdf(’Gamma’,xi,k,b);

Answer 24

evaluate the inverse cumulative PDF (this PDF has two parameters k and b)

Question 25

histogram([1,1,3,3,3,5,7,8,12],5,’BinLimits’,[0,20])

Answer 25

counts in each bin

Question 26

i=0:40
1-sum(exp(-30)*30.^i./factorial(i))
1-cdf(’Poisson’,40,30)

Answer 26

answers: what is the probability of randomly selecting 10 unit areas that contain greater than 40 defects?

Question 27

1-cdf(’Poisson’,40,30)

Answer 27

Matlab cumulative Poisson PDF