Using the pandas library in python for creating dataframes, the required expression to calculate the required probability is
- df = dataframe which holds the entire data
- wheel1 = column for the values of wheel 1
- wheel2 = columns for the values of wheel 2
<u>Subsetting columns using pandas</u> :
Rows where wheel 1 is less than 6 ;
- (df['wheel1'] < 6)
Rows where wheel 2 is greater than 6 ;
- (df['wheel2'] > 6)
<u>Combining the two conditions</u> :
(Wheel < 6 and wheel 2 > 6)
- ((df['wheel1'] < 6) & (df['wheel2'] > 6))
<u>Subsetting the condition into the entire dataframe ; such that we have the required outcome </u>
- reqout = df[((df['wheel1'] < 6) & (df['wheel2'] > 6))]
<u>Recall</u> :
- Probability =
To obtain the number of each outcomes, we use the len function, which gives the <em>length of observations in a dataframe. </em>
P(at_least_6_or_greater_than_6) =
Therefore, expression for the estimate of the probability is
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