Question

Below is what I am working. The first two screen caps are from Codio a program we use online at my school. I have been running my code through Python 3 to make sure it works before submitting my assignments; usually I have little to no issues. But now I am stuck on this one problem. Please help.

Step 4: Construct confidence interval for population proportion Construct a 99% confidence interval for the proportion of months with rice production above 307200 cwt (Company1>307200.0). In order to perform this function, you need to make the appropriate modifications to the provided script. In other words, you should Comment lines 17-52 Comment lines 56 - 89 Uncomment lines 94-100 Replace ???DATASET_NAME??? with production Replace 277VARIABLE_NAME???' with the variable 'Company1' Replace ??2Xvalue??? with the appropriate value ##Step 4: Construct confidence interval for population proportion print ('Confidence Interval - Step 4') n (production) [L' Companyl']] .count() x = (production) [['Company 1 ' ]] > 36729θ ·values.sun() stderror - (p . (1 - p)/n)*e.:s print (st.norm.interval (0.99, p, stderror)) print ) Python 3 Trinkets The easiest way to use the full power of Python 3. 四Remix +Powered by Otrinket く> main.py inflammation-01.csv File "/tmp/sessions/ac364fc4c9be04ce 1 print ('Confidence Interval -Step 4) 2 n. (production[["Company!נני .count() 3 x (production['Company1']]>387200.values.sum() /main.ру", line 3 x(production[I'Company1'11>307200 5 stderror-(p(1 p)/n)0.5 6 print (st.norm.interval (.99, p, stderror)) print .values.sum() SyntaxError: invalid syntax

Answer 1

actually you forget close the PARENTHESIS

of 2nd and 3rd line x and n values.

you are open the PARENTHESIS but you didn't close the PARENTHESIS.

so that's why you get syntax error.and you must open the files based on the column names

you able to do operations.

code:

File Edit Search View Encoding Language Settings Tools Macro Run Plugins Window? bel.py dish py ord py k py namana.csv import pandas as pd Erom scipy import stats print(" Confidence Interval-step 4") production-pd. read csv("filename.csv") S n (production[" companyl"].count )) 6 x= (production [production [ 'company1"]x307200] ['company! ' ] . sum ( ) ) stderror-(p (1-p)/n)*0.5 print (stats.norm.interval (0.99,p,stderror)) 9 10 print 12

#in plain text format

import pandas as pd
from scipy import stats
print("Confidence Interval-step 4")
production=pd.read_csv("filename.csv")
n=(production["company1"].count())
x=(production[production['company1']>307200]['company1'].sum())
p=x/n*1.0
stderror=(p*(1-p)/n)**0.5
print(stats.norm.interval(0.99,p,stderror))
print(' ')

#if you have any doubts comment below..