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Inherently synchronous motors:

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The effective resistance of a 2200 V, 50 Hz, 440 kVA, 1-phase alternator is 0.5 Ω. On short circuit, a field current of 40 A gives the full load current of 200 A. The electromotive force on open circuit with the same field excitation is 1160 V. Calculate the synchronous reactance and round it to 2 decimal places.
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Ali is the Chairman of a committee. In how many ways can a committee of 5 be chosen from 10 people given that Ali must be one of them?

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The average life of a fridge compressor motor is 10 years, with a standard deviation of 2 years. If the manufacturer is willing to replace only 3% of the motor because of failures, how long a guarantee should the manufacturer offer?

Assume that the lives of the motors follow a normal distribution.

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An internet outage (internet blackout) in Pulau Pinang occurs according to a Poisson distribution with an average of 3 failures every twenty weeks. Calculate the probability that there will not be more than one failure during a particular week.

(Hint: A Poisson distribution with mean has probability mass function )

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A production process produces thousands of temperature transducers. Let denote the number of nonconforming transducers in a sample of size 30 selected at random from the process. Which of the following is a reasonable probability model for ?

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Which best describes aggregation in data analysis?

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After grouping and aggregating, what typically happens to the number of rows in the dataset?

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What will be the output of the following code?

import pandas as pd

data = {'Category': ['A', 'A', 'B', 'B', 'C'],

             'Value': [5, 15, 25, 35, 45],

             'Score': [2, 4, 6, 8, 10]}

df = pd.DataFrame(data)

result = df.groupby('Category').agg({'Value': 'sum', 'Score': 'mean'})

print(result)

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What will be the output of the following code?

import pandas as pd

data = {'Category': ['A', 'A', 'B', 'B', 'C'],

              'Subcategory': ['X', 'Y', 'X', 'Y', 'X'],

              'Value': [10, 20, 30, 40, 50]}

df = pd.DataFrame(data)

result = df.pivot(index='Category', columns='Subcategory', values='Value')

print(result)

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