Data set exercise #2. Control Charts
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Feb 20, 2024
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For this assignment you will generate two Control Charts using QI Macros. For your convenience I have included an excel data set below which you may use to create your charts. Please create a control chart for TWO of the data elements (you may choose from among any of the options). Make sure to create labels for your chart; the automatically generated labels are not, in general, appropriate for data presentation. Along with your Control Chart construction, you will provide a brief analysis of the chart. This can take the form of a brief description of your findings (no more than a paragraph is necessary).
Control Chart(s)
1.
Percentage of Patient Readmissions
2.0
3.0
4.0
5.0
6.0
1
UCL
5.
CL
2.
Control Chart Data for Percentage of Patient Readmissions tient Readmissions
The control chart above displays the percentage of patient readmission per month from January 2009 to February 2011 using IHI rules. The overall average mean for the entire data selection is 2.46% of patient readmissions, with an upper control limit of 5.25 and a lower control limit of -0.33. The control chart dislpays special cause variation in which the 1 point reaches above the UCL for June 2010 (Rule #1), followed by a trend of decreasing readmissions from June 2010 to November 2010 (rule #5).
2.
Platelet Count after Apheresis
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
33
35
37
39
41
43
45
47
49
51
53
55
57
59
61
4.1
6.1
8.1
10.1
12.1
14.1
16.1
5
UCL
14.87
CL
10.24
LCL
5.60
Control Chart Data of Platelet Counts After Apheresis Period
Platelet Count After Apheresis
The control chart above displays the platelet count after apheresis using IHI rules. The overall average mean for the entire data selection is 10.24, with an upper control limit of 14.87 and a lower control limit of 5.60. The control chart dislpays special cause variation that dispalays a
trend of 5 decreasing platelet counts from period 53 to 58.
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The first photo is the question, where the 2nd shows some problem solving strategies
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There is a small space between the orange and purple line could you please connect the two lines together also can you please make the purple line shorter and then connect the purple line to the orange line, please take out the box that says “Diesel, petrol, Diesel best fit, petrol best fit”. Also when ever I run this code the graph shows up but there are still errors that comes up could you please fix them when you are running this on MATLAB.
Please use this code on MATLAB and fix it.
% Sample data for Diesel and Petrol cars
carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Fix the random seed for reproducibility
rng(50);
% Assumed CO2 emissions for Diesel and Petrol
CO2Diesel = 25 + 5*cos(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Diesel
CO2Petrol = 20 + 5*sin(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Petrol
% Fit polynomial curves
pDiesel = polyfit(carPosition, CO2Diesel, 3);
pPetrol = polyfit(carPosition, CO2Petrol, 3);
% Generate…
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You are assigned as the head of the engineering team to work on selecting the right-sized blower that will go on your new line of hybrid vehicles.The fan circulates the warm air on the inside of the windshield to stop condensation of water vapor and allow for maximum visibility during wintertime (see images). You have been provided with some info. and are asked to pick from the bottom table, the right model number(s) that will satisfy the requirement. Your car is equipped with a fan blower setting that allow you to choose between speeds 0, 1,2 and 3. Variation of the convection heat transfer coefficient is dependent upon multiple factors, including the size and the blower configuration.You can only use the following parameters:
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With what I’m asking from you please fix it using this code using MATLAB and send back the code.
% Sample data for Diesel and Petrol cars
carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Fix the random seed for reproducibility
rng(45);
% Assumed positions of cars
CO2Diesel = 25 + 5*cos(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Diesel
CO2Petrol = 20 + 5*sin(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Petrol
% Fit polynomial curves
pDiesel = polyfit(carPosition, CO2Diesel, 3);
pPetrol = polyfit(carPosition, CO2Petrol, 3);
% Generate points for best fit lines
fitDiesel = polyval(pDiesel, carPosition);
fitPetrol =…
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Keep the same colors the same graph, basically keep everything the same just make the line with a small curve just as shown on the picture
Keep everything the same just make the line less curvy please do not change the colors of the line and the circles do not change anything besides the curve of the line.
Use this code on MATLAB and fix it.
% Sample data for Diesel and Petrol cars
carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Use the 'seed' function instead of 'rng'
seed = 50; % Define your seed here
rand('seed',seed);
% Assumed CO2 emissions for Diesel and Petrol
CO2Diesel = 25 + 5*cos(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Diesel
CO2Petrol = 20 + 5*sin(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Petrol
% Fit polynomial curves with a reduced degree of 2
pDiesel = polyfit(carPosition, CO2Diesel, 2);
pPetrol = polyfit(carPosition, CO2Petrol, 2);
% Generate points for best fit lines
fitDiesel = polyval(pDiesel, carPosition);…
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Could you please fix my code it’s supposed to look like the graph that’s on the picture. But the lines do not cross eachother at the beginning. Could you make the lines look like the lines on the graph?
Use this code in MATLAB and fix it.
% Sample data for Diesel and Petrol cars
carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Define your seed here
seed = 50;
rand('seed',seed); % Set the seed for reproducibility
% Assumed CO2 emissions for Diesel and Petrol
CO2Diesel = 25 + 5*cos(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Diesel
CO2Petrol = 20 + 5*sin(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Petrol
% Fit polynomial curves with a reduced degree of 2
pDiesel = polyfit(carPosition, CO2Diesel, 2);
pPetrol = polyfit(carPosition, CO2Petrol, 2);
% Generate points for best fit lines
fitDiesel = polyval(pDiesel, carPosition);
fitPetrol = polyval(pPetrol, carPosition);
% Plotting the data
figure;
hold on;
% Plot Diesel best fit line…
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% Sample data for Diesel and Petrol cars
carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Fix the random seed for reproducibility
rng(45);
% Assumed positions of cars
CO2Diesel = 25 + 5*cos(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Diesel
CO2Petrol = 20 + 5*sin(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Petrol
% Fit polynomial curves
pDiesel = polyfit(carPosition, CO2Diesel, 3);
pPetrol = polyfit(carPosition, CO2Petrol, 3);
% Generate points for best fit lines
fitDiesel = polyval(pDiesel, carPosition);
fitPetrol = polyval(pPetrol, carPosition);
% Plotting the data
figure; hold on;
scatter(carPosition, CO2Diesel, 'o', 'MarkerEdgeColor', [1 0.5…
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Don't use chatgpt will upvote
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Here is the code:
% Sample data for Diesel and Petrol
carPosition = linspace(1, 60, 50); % Assumed positions of cars
CO2Diesel = 25 + 5*cos(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Diesel
CO2Petrol = 20 + 5*sin(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Petrol
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fitPetrol = polyval(pPetrol, carPosition);
% Plotting the data
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hold on;
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Use this code on MATLAB and fix it.
% Sample data for Diesel and Petrol cars
carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Fix the random seed for reproducibility
rng(50);
% Assumed CO2 emissions for Diesel and Petrol
CO2Diesel = 25 + 5*cos(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Diesel
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% Generate points for best fit lines
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