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Univariate Data Analysis: concrete strength, 20 data

Updated: Sep 24, 2023

We have a dataset of 20 data, concrete strength.


We want to develop simple data analysis, including:

  • statistics of the samples

  • histograms

  • empirical cdf

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import numpy as np import matplotlib.pyplot as plt import OpenStat as sta


#===================

DATA SUMMARY

#===================

data=np.loadtxt('concrete20.dat') d=sta.data1(data)

#d is the object collecting the dataset

data=d.data d.disp_summary()














#===================

#===================

edges=[23, 26, 29, 32, 35, 38, 41] edges=np.array(edges)


#Number of observations d.plot_hist(bins=edges,stat='count')

#bins=edges: limits of the bins #stat='count': number of observations at each bin #color='blue': color of the bars d.ax.set_xlim(23,41) d.ax.set_xticks(edges) d.ax.set_xlabel('$f_c \ MPa$') d.ax.set_title('Concrete strength n=20')











#Relative frequency d.plot_hist(bins=edges, stat='probability')

#bins=edges: limits of the bins #stat='count': number of observations at each bin d.ax.set_xlim(23,41) d.ax.set_xticks(edges) d.ax.set_xlabel('$f_c \ MPa$') d.ax.set_title('Concrete strength n=20')












==================

#===================

d.plot_cdf_emp()

#plot the empirical cdf d.ax.set_xlim(23,41) d.ax.set_ylim(0,1) d.ax.set_xlabel('$f_c \ MPa$') d.ax.set_ylabel('ecdf') d.ax.set_title('Concrete strength n=20')












d.plot_quantile_emp() #plot the empirical quantile function d.ax.set_xlabel('$probability$') d.ax.set_ylabel('f_c \ MPa') d.ax.set_xlim(0,1) d.ax.set_ylim(23,41) d.ax.set_xlabel('$probability$') d.ax.set_ylabel('$f_c \ MPa$')













concrete20
.txt
Download TXT • 360B

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