BADM 211 Test 1 - Quizzes
Classification and prediction are two types of Unsupervised learning.
True, in both the problems an outcome variable is specified
False, in both the problems an outcome variable is specified
True, neither has an outcome variable specified
False, neither has an outcome variable specified - answerFalse, in both the problems
an outcome variable is specified
Which of the following is an example of supervised learning?
A store manager, under the supervision of her manager, attempting to group customers
into a few segments.
A newbie data scientist tasked with reducing the number of predictors based on the
correlation among them.
A store manager, without any supervision from her manager, attempting to predict sales
for tomorrow.
A seasoned data scientist attempting to develop a new algorithm to create
multidimensional charts. - answerA store manager, without any supervision from her
manager, attempting to predict sales for tomorrow.
Why would we partition our data into train and validation partitions?
To fit separate models on each partition and compare models for their performance
To test the model performance on data that has not been used to develop the model
Because the data could be too large to work with
To fit different models on the two datasets and take average performance of the two
models - answerTo test the model performance on data that has not been used to
develop the model
Which of the following could be a likely cause of overfitting?
Too many predictors
, Too many rows in the data
Many predictors are correlated
Almost none of the predictors are correlated to each other - answerToo many predictors
Which of the following is always true with respect to outliers?
a. Outliers are the values that are over three standard deviation away from the mean
b. Outliers are invalid data points
Only A
Only B
Both A and B
Neither A nor B - answerOnly A
Which of the following statements are true?
a. Principal component analysis (PCA) involves reducing the number of records.
b. Principal component analysis (PCA) involves reducing the number of columns
(variables).
c. Clustering involves separating the records into different groups.
d. Clustering involves reducing the number of columns.
Both A and B
Both B and C
Both C and D
Both B and D - answerBoth B and C
Classification and prediction constitute:
Predictive analytics
Prescriptive analytics
Descriptive analytics
Exploratory Analysis - answerPredictive analytics
Which statement is true regarding prediction and classification problems?
Predicting whether it would rain tomorrow is an example of classification problem.
Prediction is concerned with predicting a categorical outcome while classification is
concerned with grouping similar observations together.
Predicting whether it would rain tomorrow is an example of prediction problem.
Classification and prediction are two types of Unsupervised learning.
True, in both the problems an outcome variable is specified
False, in both the problems an outcome variable is specified
True, neither has an outcome variable specified
False, neither has an outcome variable specified - answerFalse, in both the problems
an outcome variable is specified
Which of the following is an example of supervised learning?
A store manager, under the supervision of her manager, attempting to group customers
into a few segments.
A newbie data scientist tasked with reducing the number of predictors based on the
correlation among them.
A store manager, without any supervision from her manager, attempting to predict sales
for tomorrow.
A seasoned data scientist attempting to develop a new algorithm to create
multidimensional charts. - answerA store manager, without any supervision from her
manager, attempting to predict sales for tomorrow.
Why would we partition our data into train and validation partitions?
To fit separate models on each partition and compare models for their performance
To test the model performance on data that has not been used to develop the model
Because the data could be too large to work with
To fit different models on the two datasets and take average performance of the two
models - answerTo test the model performance on data that has not been used to
develop the model
Which of the following could be a likely cause of overfitting?
Too many predictors
, Too many rows in the data
Many predictors are correlated
Almost none of the predictors are correlated to each other - answerToo many predictors
Which of the following is always true with respect to outliers?
a. Outliers are the values that are over three standard deviation away from the mean
b. Outliers are invalid data points
Only A
Only B
Both A and B
Neither A nor B - answerOnly A
Which of the following statements are true?
a. Principal component analysis (PCA) involves reducing the number of records.
b. Principal component analysis (PCA) involves reducing the number of columns
(variables).
c. Clustering involves separating the records into different groups.
d. Clustering involves reducing the number of columns.
Both A and B
Both B and C
Both C and D
Both B and D - answerBoth B and C
Classification and prediction constitute:
Predictive analytics
Prescriptive analytics
Descriptive analytics
Exploratory Analysis - answerPredictive analytics
Which statement is true regarding prediction and classification problems?
Predicting whether it would rain tomorrow is an example of classification problem.
Prediction is concerned with predicting a categorical outcome while classification is
concerned with grouping similar observations together.
Predicting whether it would rain tomorrow is an example of prediction problem.
