Plot mean and standard deviations along with data on a bell curve

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Sunshine
Sunshine 2020-5-21
评论： Image Analyst 2020-6-19
I have columns of data, numbering approximately 120 rows. The data is 1 thru 5, representing survey data. I am working on analyzing the data columns. The column data also has some NaN. I can calculate the mean and standard deviations. However, I am attempting to plot the mean, standard deviations, along with the actual data on the bell curve. I found this code that at least plots the data. But I am not sure how to change the code to correctly represent my data on a bell curve. For instance, I don't think I need the randn function, given the amount of data I have. In short, I just want to plot my data, the mean, and standard deviations (to plus and minus 3 sigma) for all columns of data on the bell curve, similar to what this code produces.
x = .03*randn(10000,1)+.34;
[N,X] = hist(x,100);
hfig = figure;
bar(X,N)
hold on;
y = [0 1.2*max(N)];
center = mean(x);
std1 = std(x);
%center plot
plot([center center],y,'r-.')
%1 std
plot([center center]+std1,y,'g-.')
plot([center center]-std1,y,'g-.')
%2 std
plot([center center]+2*std1,y,'k-.')
plot([center center]-2*std1,y,'k-.')
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Sunshine
Sunshine 2020-6-19
Thanks a bunch! This really worked well for me. I was also able to modify the code to include additional standard deviations.
I am curious. I found code and modified it to what you see below. My goal is to calculate the percentages of the data for column p1. So for instance, I want to determine how much of the data in a particular column are 5s, 4s, 3s, etc.
Code
numberOfBins = max(personality_cols.p1(:));
countsPercentage = 100 * hist(personality_cols.p1(:), numberOfBins) / numel(personality_cols.p1)
Answer
countsPercentage =
9.0909 4.1322 13.2231 33.0579 24.7934
The countsPercentage does not equal 100. countsPercentage's total = 84.3. Is the remaining percentage NaN values? How do I get the percentage of the NaN values to know that the other percentages are correct? How do I exclude NaN values from the countsPercentage values so that 100 percent is only looking at data (5s, 4s, 3s, etc)? How do I know which values are being represented by which set of data (for example, how do I know 9.0909 are 1s or are they 5s from the p1 column data)?
Image Analyst
Image Analyst 2020-6-19
You can use the isnan() function along with sum() to compute the number of nans in a vector.
numNans = sum(isnan(yourVector));
percentNans = 100 * numNans / numel(yourVector);

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回答（1 个）

Image Analyst
Image Analyst 2020-5-22
Then if it's not normally distributed data, why do you want to fit a bell curve to it?
Did you try fitdist():
load hospital
x = hospital.Weight;
pd = fitdist(x,'Normal')
x_values = 50:1:250;
y = pdf(pd,x_values);
plot(x_values,y,'LineWidth',2)

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