How to Get Expected Defectives in Minitab Binomial Capability Analysis

@leavor Minitab has excellent technical support. Have you checked with them directly? I have notified them of this post in the meantime.

Thank you for your help!

I have drawn Binomial Plot according to the provided help document

I am using Python and my code is as follows:

# -*- coding: utf-8 -*-
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Created on Thu Aug 13 11:20:54 2020
@author: leavor
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import pandas as pd
from collections import Counter
from scipy.stats import binom
from matplotlib import pyplot as plt
data = pd.Series([12,10,15,11,10,14,15,13,11,14,11,13,13,12,11,11,15,10,11,15,12,13,
12,13,14,12,13,13,10,12],name=’Defectives’)#Defectives
sampleSize = 20#sample size const
N = len(data)#N
collec = Counter(data)
key = list(collec.keys())#Observed Defectives
freq = list(collec.values())#Frequency
df = pd.DataFrame({‘OD’:key,’Freq’:freq})
df = df.sort_values(by=’OD’)
tmp = pd.Series([1]).append(df[‘Freq’])
df[‘Indicator’] = tmp.cumsum().iloc[:-1].values#Indicator
df[‘Rank’] = (2*df[‘Indicator’]+df[‘Freq’]-1)/2#Rank
df[‘ECDF’] = (df[‘Rank’]-0.375)/(N+0.25)#ECDF
p = data.sum()/(N*sampleSize)#AverageProportion
df[‘ED’] = binom.ppf(df[‘ECDF’],sampleSize,p)#expected defectives
plt.scatter(df[‘OD’],df[‘ED’])
plt.plot(df[‘OD’],df[‘OD’],color=’r’,linewidth=0.8)
plt.xlabel(‘Observed Defectives’)
plt.xlabel(‘Expected Defectives’)
plt.title(‘Binomial Plot’)

You can use the same steps as outlined in the document I attached before, with 2 changes:

• For step 5, calculate the average number of defects.
• For step 6, use Calc > Probability Distributions > Poisson.  For the Mean, enter the number computed from step 5.