In [1]:

    

###### Use this function to calculate stand concentrations. ############################
## Leave the function alone 
function concentrations = serialDilution(stock, pipettes, flasks)
    concentrations =[];
    for i = 1:length(pipettes)
        if i == 1
            concentrations(i) = stock * pipettes(i)/flasks(i);  # calculate first dilution
        else
            concentrations(i) = concentrations(i-1) * pipettes(i)/flasks(i); # calculate all other dilutions
        end
    end
    concentrations = flip(concentrations)'; # reverse the vector from lowest to highest and transpose to column vector
end
########################################################################################


    

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####### Insert standard info here ######################################################
## insert correct values as arguments to serialDilution() below
concentrations = serialDilution(stock, pipettes, flasks); # conc in ppm, volume of pipettes in ml, vol of flasks in ml 

disp("Standard Concentrations (in ppm) = ");
output_precision(4); # display 4 sig figs - change if needed
disp(concentrations);


    

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######## Insert QC Info Here ############################################################
qc_stock   = 100.6;  # units: ppm, insert concentration of the stock soln. used for QC
qc_pipette = 10;     # units: ml
qc_flask   = 50;     # units: ml (must be same length and units as 'qc_pipette')
########################################################################################

qc_conc    = qc_pipette / qc_flask * qc_stock;
disp("QC Concentration (in ppm) = ");
output_precision(4);  # display 4 sig figs - change if needed
disp(qc_conc);


    

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#### Import the data
## Input your datafile name (and/or path) in the csvread() function below
X = csvread('data/your-datafile-name.csv'); ## import data
X(1:2, :) ## print to screen to make sure data imported OK (optional)


    

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wavelengths = X(:, 1); ## extract wavelength column to it's own vector
X = X(:, 2:2:end); ## extract even columns (intensity columns) and discard wavelength columns
X(1:2, :) ## print to screen to make sure clean up worked as expected (optional)


    

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##### Plot the emission spectrum

plot(wavelengths, X(:, 5), 'DisplayName', 'Name of Sample');
xlabel('Wavelength (nm)');
ylabel('Intensity (arbitrary)');
xlim([380 700]); ylim([0 0.25]);
hold on
plot(wavelengths, X(:, 9), 'DisplayName', 'Name of Sample');
legend();
hold off


    

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##### find max emission wavelength #######################
[max_values indices] = max(X(:, 5));
lambda_max = wavelengths(indices);
disp("Wavelength of maximum emission (in nm) = ");
output_precision(0); # only display to nearest nm
disp(lambda_max);


    

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disp("The intensities at the analytical wavelength are:")
intensity_values =  X(wavelengths == (lambda_max), :)


    

In [118]:

    

##### Define function to calculate linear fit and R2 ###############################
##### Leave this section alone

function [fit_params, r2, fitline] = fitlm(x, y)
    X = [ones(length(x), 1) x];
    fit_params = (pinv(X'*X))*X'*y;
    # watch this video to understand this code: https://www.youtube.com/watch?v=w2FKXOa0HGA
    ss_tot = sum((y - mean(y)).^2);
    ss_reg = sum(((X*fit_params) - mean(y)).^2);
    r2 = ss_reg/ss_tot;
    fitline = [x, X*fit_params];
end
#####################################################################################


    

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standards = intensity_values(4:6) .- intensity_values(1); ## subtract blank reading 
### (Choose the correct columns above by number)

##### Plot Data

plot(concentrations', standards', '*', 'DisplayName', 'Experimental Data');
xlabel('Concentration (ppm)');
ylabel('Intensity (arbitrary)');

##### Calculate linear model / cal curve
[fit_params, r2, fitline] = fitlm(concentrations, standards');

##### Plot cal curve
hold on; # this keeps our previous plot of the training data visible
plot(fitline(:, 1), fitline(:, 2), 'b--', 'DisplayName', 'Linear regression')
legend('location', 'northwest')
hold off # Don't put any more plots on this figure

##### print values to screen
output_precision(4); # only display to 4 sf
disp("Slope =")
disp(fit_params(2))
disp("Intercept =")
disp(fit_params(1))
disp("R2 =")
disp(r2)


    

In [120]:

    

###### Calculate concentration of samples & QC

samples_qc = intensity_values(7:12) .- intensity_values(1); ## Subtract blank - Choose the correct columns here by number
concs = ### insert code here to calculate concentrations


    

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###### Calculate mean QC value
mean_qc = mean(concs(1:3));   ## Choose correct QC columns
sd_qc   = std(concs(1:3));    ## Choose correct QC columns
qc_percent_diff = ## Insert code here to calculate percent difference

output_precision(1);  # display 1 decimal - change if needed

disp("Avearge  [Quinine] in QC (in ppm) = ");
disp(mean_qc);

disp("Expected [Quinine] in QC (in ppm) = ");
disp(qc_conc);

disp("QC Difference in percent = ");
disp(qc_percent_diff);


    

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###### Calculate mean sample values

mean_samples = ## Calculate sample mean here
sd_samples = ## Calculate SD here

# Display average sample conc.
disp("Avearge  [Quinine] in sample (in ppm) = ");
disp(mean_samples);

## Display sample SD.
##### Fill in code here

## Display sample RSD
##### Fill in code here


    

In [130]:

    

mean_blank = mean(intensity_values(1:3)); ## Choose correct blank columns
sd_blank   = std(intensity_values(1:3));  ## Choose correct blank columns

## Do calculations here...