Question

It is known that 60% of the days have solar power generation in City A solar farm above 43.0 kWh (cityA>43.0). Is there sufficient evidence to suggest that the proportion is less than 60%? Test at 5% level of significance. In order to perform this function, you need to make the appropriate modifications to the provided script. In other words, you should:

Comment lines 94 - 100
Comment lines 106 - 113
Uncomment lines 119 - 125
Replace ???DATASET_NAME??? with solarkwh
Replace '???VARIABLE_NAME???' with the variable 'cityA'
Replace ???Xvalue??? with the appropriate value
Replace ???NULL_VALUE??? with the appropriate value for the null hypothesis
Replace '???TEST_TYPE???' with the appropriate alternative hypothesis
----------------------------------------------------------------

The code they give:

print ('Hypothesis Test - Step 6')
n = ???DATASET_NAME???[['???VARIABLE_NAME???']].count()
x = (???DATASET_NAME???[['???VARIABLE_NAME???']] > ???Xvalue???).values.sum()
null_value = ???NULL_VALUE???
alternative = '???TEST_TYPE???'
print (prop_1samp_ztest(x, n, null_value, alternative))
print ('')

Here is what i have,

print ('Hypothesis Test - Step 6')
n = solarkwh[['cityA']].count()
x = (solarkwh[['cityA']] > 43.0).values.sum()
null_value = 43
alternative = 'larger'
print (prop_1samp_ztest(x, n, null_value, alternative))
print ('')

I am not sure exaclty what they want for the variables they have given me (Null_value, alternative and Xvalue)

Answer 1

We need to test for the proportion is less than 60%. So,

Null hypothesis H0: p = 0.6

Alternative hypothesis H1: p < 0.6

Hence,

Null_value = 0.6 , alternative = 'smaller' and Xvalue = 43.0

The code should be modified like this,

print ('Hypothesis Test - Step 6')
n = solarkwh[['cityA']].count()
x = (solarkwh[['cityA']] > 43.0).values.sum()
null_value = 0.6
alternative = 'smaller'
print (prop_1samp_ztest(x, n, null_value, alternative))
print ('')