%% Import data
 raw_data = readtable('data.txt');
 %*****Question 1 - try the following line:
 % uiimport('data.txt'); % opens up a GUI for data details
 % Please pay attention to different columns, and try to understand the
 % data structure
 
 % Select column 8/9/10 for downstream analysis
 table_data = raw_data(:, 8:10); 
 % convert table format to array
 data = table2array(table_data);
 %*****Question 2 - try using 'help' function to understand 'table2array'
 
 %% Data processing
 % basic info about the raw data
 % raw_data{:,1} - name 
 % raw_data{:,2} - sex
 % raw_data{:,3} - note
 % raw_data{:,4} - number of subject
 % raw_data{:,5} - subject age
 % raw_data{:,6} - (experimental) block number
 % raw_data{:,7} - trial number
 % raw_data{:,8} - motion conditions: 
 %    ==1 - continuous motion; ==2 - motion with stop
 % raw_data{:,9} - sound conditions:
 %    ==1 - sound absent; ==2 - sound present
 % raw_data{:,10} - bounce responses (dependent variable)
 
 % after the column selection:
 % raw_data{:,8} == data(:,1);
 % raw_data{:,9} == data(:,2);
 % raw_data{:,10} == data(:,3);
 
 N = 10; % sample size
 m = zeros(2, 2); 
 m(1,1) = mean(data(data(:,1)==1 & data(:,2)==1, 3)); % continuous motion no sound
 m(1,2) = mean(data(data(:,1)==1 & data(:,2)==2, 3)); % motion with stop
 m(2,1) = mean(data(data(:,1)==2 & data(:,2)==1, 3)); % sound absent
 m(2,2) = mean(data(data(:,1)==2 & data(:,2)==2, 3)); % sound present
 %*****Question 3 - what is 'm'? 
 
 err = zeros(2,2);
 err(1,1) = std(data(data(:,1)==1 & data(:,2)==1, 3))/sqrt(N); % continuous motion
 err(1,2) = std(data(data(:,1)==1 & data(:,2)==2, 3))/sqrt(N); % motion with stop
 err(2,1) = std(data(data(:,1)==2 & data(:,2)==1, 3))/sqrt(N); % sound absent
 err(2,2) = std(data(data(:,1)==2 & data(:,2)==2, 3))/sqrt(N); % sound present
 %*****Question 4 - what is 'err'? 
 %*****Question 5 - what does the function 'sqrt' do?
 
 %% Data visualization
 % using barweb (bar graph with error bars) 
 % https://www.mathworks.com/matlabcentral/fileexchange/10803-barweb-bargraph-with-error-bars
 barweb(m, err, [], {'without stop', 'with stop'}, [], {'kind of motion'}, ... 
 {'percent bouncing'}, [], [], {'no sound', 'sound'})

 %*****Question 6 - understand all the parameters feeding in 'barweb'
figure(1);
 %*****Quesiton 7 - adjust the figure legends / colours of your own choice,
 %and save the figure with .png format
 
 %*****Question 8 - how to change the percentage from 0.1-1 to 10%-100%?
 
 %*****Question 9 - reflection of the underlying experiment:
 %read the original paper thoroughly and compare the original result with
 % the figure you produced.