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Part C (Based off week 12 workshop content) Since the implementation of the CityCycle scheme in October 2010, the Bris- bane

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IF YOU HAVE ANY DOUBTS COMMENT BELOW I WILL BE TTHERE TO HELP YOU..ALL THE BEST..

AS FOR GIVEN DATA.

Matlab:

%Linear Regression
clc
M = csvread('CityCycleData.csv',1,0); %reading and storing in M
x = M(:,1); %Month number
y = M(:,2); %Total City Cycle Trips

figure, hold on
scatter(x,y)
% Yes from scatter plot we can see that the trend is approximately linear
% equation is in form: y = x1*x + intercept
% and values of x1 and intercept are mentioned in table of mdl
mdl = fitlm(x,y)

%function representing our linear equation
% y = mx + c
f = @(x) x*617.97 + (-2.1062);

SE = mdl.Coefficients(:,2);
SE = SE{:,'SE'};
alpha = 1 - 95/100;
crtical = 1 - alpha/2;
%interval for intercept and x with 95% confidence
interval = SE .* crtical

%Q4
%pValue is smalller than than alpha mentioned = 0.05 (pValue < alpha)
%so we can say that from observing table that
%the numbers of tickets are affected by months.

%Q5
%total sum of squares
SS_total = sum(y - mean(y))^2;
%regression sum of squres
SS_regression = sum(f(x) - mean(y))^2;

% Proportion of total variance of trip numbers that are being accounted for
% by month
R = 1 - SS_total / SS_regression

I HOPE YOU UNDERSTAND..

PLS RATE THUMBS UP..ITS HELPS ME ALOT..

THANK YOU...!!

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