Data Science Practice Questions and
Answers 100% Correct
A certain couple tells you that they have two children, at least one of which is a girl.
What is the probability that they have two girls? - ANSWER-In the case of two children,
there are 4 equally likely possibilities
BB, BG, GB and GG;
where B = Boy and G = Girl and the first letter denotes the first child.
From the question, we can exclude the first case of BB. Thus from the remaining 3
possibilities of BG, GB & BB, we have to find the probability of the case with two girls.
Thus, P(Having two girls given one girl) = "
"
A jar has 1000 coins, of which 999 are fair and 1 is double headed. Pick a coin at
random, and toss it 10 times. Given that you see 10 heads, what is the probability that
the next toss of that coin is also a head? - ANSWER-There are two ways of choosing
the coin. One is to pick a fair coin and the other is to pick the one with two heads.
Probability of selecting fair coin = 999/1000 = 0.999
Probability of selecting unfair coin = 1/1000 = 0.001
Selecting 10 heads in a row = Selecting fair coin * Getting 10 heads + Selecting an
unfair coin
P (A) = 0.999 * (1/2)^5 = 0.999 * (1/1024) = 0.000976
P (B) = 0.001 * 1 = 0.001
P( A / A + B ) = 0.000976 / (0.000976 + 0.001) = 0.4939
P( B / A + B ) = 0..001976 = 0.5061
Probability of selecting another head = P(A/A+B) * 0.5 + P(B/A+B) * 1 = 0.4939 * 0.5 +
0.5061 = 0.7531"
"
Can you cite some examples where a false negative important than a false positive? -
ANSWER-Example 1: Assume there is an airport 'A' which has received high-security
threats and based on certain characteristics they identify whether a particular passenger
can be a threat or not. Due to a shortage of staff, they decide to scan passengers being
predicted as risk positives by their predictive model. What will happen if a true threat
customer is being flagged as non-threat by airport model?
, Example 2: What if Jury or judge decides to make a criminal go free?
Example 3: What if you rejected to marry a very good person based on your predictive
model and you happen to meet him/her after a few years and realize that you had a
false negative?"
"
Can you cite some examples where a false positive is important than a false negative? -
ANSWER-Let us first understand what false positives and false negatives are.
False Positives are the cases where you wrongly classified a non-event as an event
a.k.a Type I error.
False Negatives are the cases where you wrongly classify events as non-events, a.k.a
Type II error.
Example 1: In the medical field, assume you have to give chemotherapy to patients.
Assume a patient comes to that hospital and he is tested positive for cancer, based on
the lab prediction but he actually doesn't have cancer. This is a case of false positive.
Here it is of utmost danger to start chemotherapy on this patient when he actually does
not have cancer. In the absence of cancerous cell, chemotherapy will do certain
damage to his normal healthy cells and might lead to severe diseases, even cancer.
Example 2: Let's say an e-commerce company decided to give $1000 Gift voucher to
the customers whom they assume to purchase at least $10,000 worth of items. They
send free voucher mail directly to 100 customers without any minimum purchase
condition because they assume to make at least 20% profit on sold items above
$10,000. Now the issue is if we send the $1000 gift vouchers to customers who have
not actually purchased anything but are marked as having made $10,000 worth of
purchase."
"
Can you cite some examples where both false positive and false negatives are equally
important? - ANSWER-In the Banking industry giving loans is the primary source of
making money but at the same time if your repayment rate is not good you will not make
any profit, rather you will risk huge losses.
Banks don't want to lose good customers and at the same point in time, they don't want
to acquire bad customers. In this scenario, both the false positives and false negatives
become very important to measure."
"
Can you explain the difference between a Validation Set and a Test Set? - ANSWER-A
Validation set can be considered as a part of the training set as it is used for parameter
selection and to avoid overfitting of the model being built.
On the other hand, a Test Set is used for testing or evaluating the performance of a
trained machine learning model.
Answers 100% Correct
A certain couple tells you that they have two children, at least one of which is a girl.
What is the probability that they have two girls? - ANSWER-In the case of two children,
there are 4 equally likely possibilities
BB, BG, GB and GG;
where B = Boy and G = Girl and the first letter denotes the first child.
From the question, we can exclude the first case of BB. Thus from the remaining 3
possibilities of BG, GB & BB, we have to find the probability of the case with two girls.
Thus, P(Having two girls given one girl) = "
"
A jar has 1000 coins, of which 999 are fair and 1 is double headed. Pick a coin at
random, and toss it 10 times. Given that you see 10 heads, what is the probability that
the next toss of that coin is also a head? - ANSWER-There are two ways of choosing
the coin. One is to pick a fair coin and the other is to pick the one with two heads.
Probability of selecting fair coin = 999/1000 = 0.999
Probability of selecting unfair coin = 1/1000 = 0.001
Selecting 10 heads in a row = Selecting fair coin * Getting 10 heads + Selecting an
unfair coin
P (A) = 0.999 * (1/2)^5 = 0.999 * (1/1024) = 0.000976
P (B) = 0.001 * 1 = 0.001
P( A / A + B ) = 0.000976 / (0.000976 + 0.001) = 0.4939
P( B / A + B ) = 0..001976 = 0.5061
Probability of selecting another head = P(A/A+B) * 0.5 + P(B/A+B) * 1 = 0.4939 * 0.5 +
0.5061 = 0.7531"
"
Can you cite some examples where a false negative important than a false positive? -
ANSWER-Example 1: Assume there is an airport 'A' which has received high-security
threats and based on certain characteristics they identify whether a particular passenger
can be a threat or not. Due to a shortage of staff, they decide to scan passengers being
predicted as risk positives by their predictive model. What will happen if a true threat
customer is being flagged as non-threat by airport model?
, Example 2: What if Jury or judge decides to make a criminal go free?
Example 3: What if you rejected to marry a very good person based on your predictive
model and you happen to meet him/her after a few years and realize that you had a
false negative?"
"
Can you cite some examples where a false positive is important than a false negative? -
ANSWER-Let us first understand what false positives and false negatives are.
False Positives are the cases where you wrongly classified a non-event as an event
a.k.a Type I error.
False Negatives are the cases where you wrongly classify events as non-events, a.k.a
Type II error.
Example 1: In the medical field, assume you have to give chemotherapy to patients.
Assume a patient comes to that hospital and he is tested positive for cancer, based on
the lab prediction but he actually doesn't have cancer. This is a case of false positive.
Here it is of utmost danger to start chemotherapy on this patient when he actually does
not have cancer. In the absence of cancerous cell, chemotherapy will do certain
damage to his normal healthy cells and might lead to severe diseases, even cancer.
Example 2: Let's say an e-commerce company decided to give $1000 Gift voucher to
the customers whom they assume to purchase at least $10,000 worth of items. They
send free voucher mail directly to 100 customers without any minimum purchase
condition because they assume to make at least 20% profit on sold items above
$10,000. Now the issue is if we send the $1000 gift vouchers to customers who have
not actually purchased anything but are marked as having made $10,000 worth of
purchase."
"
Can you cite some examples where both false positive and false negatives are equally
important? - ANSWER-In the Banking industry giving loans is the primary source of
making money but at the same time if your repayment rate is not good you will not make
any profit, rather you will risk huge losses.
Banks don't want to lose good customers and at the same point in time, they don't want
to acquire bad customers. In this scenario, both the false positives and false negatives
become very important to measure."
"
Can you explain the difference between a Validation Set and a Test Set? - ANSWER-A
Validation set can be considered as a part of the training set as it is used for parameter
selection and to avoid overfitting of the model being built.
On the other hand, a Test Set is used for testing or evaluating the performance of a
trained machine learning model.
