%Lab 23 Solutions
%MatLab - Data analysis with polyfit
%and more plotting
%Patrick D. Schmid

clear;

%load the data file
load golfdata.txt;

%the data we want is in columns, so
driving = golfdata(:,1);
scoring = golfdata(:,2);
putting = golfdata(:,3);
birdies = golfdata(:,4);
money = golfdata(:,5);

%best fit straight lines
%let's make use of ans
polyfit(driving, money, 1);
drivingLine = ans(1) * driving + ans(2);

%calculcate average absolute error
drivingError = mean(abs(money-drivingLine))

polyfit(scoring, money, 1);
scoringLine = ans(1) * scoring + ans(2);
scoringError = mean(abs(money-scoringLine))

polyfit(putting, money, 1);
puttingLine = ans(1) * putting + ans(2);
puttingError = mean(abs(money-puttingLine))

polyfit(birdies, money, 1);
birdiesLine = ans(1) * birdies + ans(2);
birdiesError = mean(abs(money-birdiesLine))

%let's plot all factors
figure(1)
plot(driving, money, 'ro', driving, drivingLine, 'b-')
xlabel('driving'), ylabel('money')
title('Driving vs. Money')

figure(2)
plot(scoring, money, 'ro', scoring, scoringLine, 'b-')
xlabel('scoring'), ylabel('money')
title('Scoring vs. Money')

figure(3)
plot(putting, money, 'ro', putting, puttingLine, 'b-')
xlabel('putting'), ylabel('money')
title('Putting vs. Money')

figure(4)
plot(birdies, money, 'ro', birdies, birdiesLine, 'b-')
xlabel('birdies'), ylabel('money')
title('Birdies vs. Money')