DATA MINING PRACTICE EXAM #1
QUESTIONS WITH CORRECT
ANSWERS
Which of the following statements are correct for Logistic Regression?
(i) Logistic Regression is used for a classification problem, where the target variable
is categorical.
(ii) Logistic Regression is an example of unsupervised learning.
(iii) Logistic Regression is used for predicting a quantitative variable since it has the
word regression in its name. - Answer-i only
We are interested in making a bet with a friend. The probability of success (winning
the bet) is 0.75.
What are the odds of success? - Answer-3
We are interested in making a bet with a friend. The probability of success (winning
the bet) is 0.75.
What are the odds of failure? - Answer-1/3
We are building a model to predict whether an F1 car will win the race. The average
speed of the car (miles per hour) is our only feature.
We run a logistic regression model and find that b0 = -3, b1 = 0.015.
What is the meaning of b0 in this model? - Answer-log odds of winning when avg car
speed is 0
We are building a model to predict whether an F1 car will win the race. The average
speed of the car (miles per hour) is our only feature.
We run a logistic regression model and find that b0 = -3, b1 = 0.015.
What is the meaning (interpretation) of b1 in this model? - Answer-If avg speed
increases by one unit, log odds of winning change by b1
Which type of data mining problem is it:
Predicting the daily new COVID-19 cases in Iowa - Answer-Regression
Data Mining is focused on extracting/collecting data for analysis - Answer-False
During the Data Prep step of CRISP-DM, we might have to merge data from different
tables into a single table for modeling. - Answer-True
What is the type of feature:
Tesla stock price (sample values: $190, $ 80, $220, etc) - Answer-Numeric
There is a dataset called "students' transcripts" that looks like the one below. This
dataset will be later combined with other datasets containing students' information, in
order to predict the income of students' first job after they graduate. It contains
students' grades for two courses they have taken. Data Mining is a course that every
QUESTIONS WITH CORRECT
ANSWERS
Which of the following statements are correct for Logistic Regression?
(i) Logistic Regression is used for a classification problem, where the target variable
is categorical.
(ii) Logistic Regression is an example of unsupervised learning.
(iii) Logistic Regression is used for predicting a quantitative variable since it has the
word regression in its name. - Answer-i only
We are interested in making a bet with a friend. The probability of success (winning
the bet) is 0.75.
What are the odds of success? - Answer-3
We are interested in making a bet with a friend. The probability of success (winning
the bet) is 0.75.
What are the odds of failure? - Answer-1/3
We are building a model to predict whether an F1 car will win the race. The average
speed of the car (miles per hour) is our only feature.
We run a logistic regression model and find that b0 = -3, b1 = 0.015.
What is the meaning of b0 in this model? - Answer-log odds of winning when avg car
speed is 0
We are building a model to predict whether an F1 car will win the race. The average
speed of the car (miles per hour) is our only feature.
We run a logistic regression model and find that b0 = -3, b1 = 0.015.
What is the meaning (interpretation) of b1 in this model? - Answer-If avg speed
increases by one unit, log odds of winning change by b1
Which type of data mining problem is it:
Predicting the daily new COVID-19 cases in Iowa - Answer-Regression
Data Mining is focused on extracting/collecting data for analysis - Answer-False
During the Data Prep step of CRISP-DM, we might have to merge data from different
tables into a single table for modeling. - Answer-True
What is the type of feature:
Tesla stock price (sample values: $190, $ 80, $220, etc) - Answer-Numeric
There is a dataset called "students' transcripts" that looks like the one below. This
dataset will be later combined with other datasets containing students' information, in
order to predict the income of students' first job after they graduate. It contains
students' grades for two courses they have taken. Data Mining is a course that every
