BADM 211 EXAM 1 QUESTIONS WITH 100%
VERIFIED ANSWERS 2025/26
1 of 47
Term
What are the main types of categorical variables and
how can we code them?
Give this one a try later!
Can be coded using text or numerically; categorical variables must be
converted for the computer to process them
Ordinal- can replace text with integers preserving the ranking
between categories- ordering categories (rankings, order, or
scaling)
Nominal- create dummy variables (is female or is male, and
female or male is converted to 0 or 1) categories with no ordering
or direction
, can be used to compare a single statistic across groups; each bar
represents a group, the length of the bar is proportional to the value
of the statistics
Captures many common machine learning problems, goal is to give
the correct label to an instance; prediction is similar to classification
but it emphasizes
predicting the value of a numerical variable (i.e. amount of purchase)
rather than purchaser or non purchaser.
Prediction: refers to the prediction of the value of a continuous variable
(estimation & regression are sometimes used to refer to prediction of
the value of a variable)
1. Volume (size)
2. Velocity (speed)
3.Variety (structured or not)
4.Veracity (quality)
Don't know?
2 of 47
Term
What is a classification problem?
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The process of finding a model that describes and distinguishes data
classes and concepts. The problem requires identifying which
category an observation belongs to on the basis of a training set of
data containing
observations whose categories are known. Ex. wanting to predict
the probability of rain tomorrow.
, the science of transforming data into insights and models that lead to
better decisions and add value to individuals, companies and
societies.
a special type of bar chart that displays the distribution of a numerical
value; we use them to check whether a numerical variable has a
specific distribution such as normal distribution (x-axis: numerical
value, potentially "binned") (y-axis: counts of that same variable)
when there is no outcome to predict or classify; goal is to find associations
and patterns; made up of association rules, dimension reduction,
clustering,
collaborative filling (personalized Netflix recommendations) and
affiliation analysis
Don't know?
3 of 47
Term
One way of dealing with missing values is by
Give this one a try later!
data deletion; by removing data averaging; by using the
entire records with missing average of all variables
values
data imputation; by
replacing the mean or
data duplication; by median of the
replicating existing values non-missing records for
for consistency that variable (can use
linear
regression), another way is
, omission.
VERIFIED ANSWERS 2025/26
1 of 47
Term
What are the main types of categorical variables and
how can we code them?
Give this one a try later!
Can be coded using text or numerically; categorical variables must be
converted for the computer to process them
Ordinal- can replace text with integers preserving the ranking
between categories- ordering categories (rankings, order, or
scaling)
Nominal- create dummy variables (is female or is male, and
female or male is converted to 0 or 1) categories with no ordering
or direction
, can be used to compare a single statistic across groups; each bar
represents a group, the length of the bar is proportional to the value
of the statistics
Captures many common machine learning problems, goal is to give
the correct label to an instance; prediction is similar to classification
but it emphasizes
predicting the value of a numerical variable (i.e. amount of purchase)
rather than purchaser or non purchaser.
Prediction: refers to the prediction of the value of a continuous variable
(estimation & regression are sometimes used to refer to prediction of
the value of a variable)
1. Volume (size)
2. Velocity (speed)
3.Variety (structured or not)
4.Veracity (quality)
Don't know?
2 of 47
Term
What is a classification problem?
Give this one a try later!
The process of finding a model that describes and distinguishes data
classes and concepts. The problem requires identifying which
category an observation belongs to on the basis of a training set of
data containing
observations whose categories are known. Ex. wanting to predict
the probability of rain tomorrow.
, the science of transforming data into insights and models that lead to
better decisions and add value to individuals, companies and
societies.
a special type of bar chart that displays the distribution of a numerical
value; we use them to check whether a numerical variable has a
specific distribution such as normal distribution (x-axis: numerical
value, potentially "binned") (y-axis: counts of that same variable)
when there is no outcome to predict or classify; goal is to find associations
and patterns; made up of association rules, dimension reduction,
clustering,
collaborative filling (personalized Netflix recommendations) and
affiliation analysis
Don't know?
3 of 47
Term
One way of dealing with missing values is by
Give this one a try later!
data deletion; by removing data averaging; by using the
entire records with missing average of all variables
values
data imputation; by
replacing the mean or
data duplication; by median of the
replicating existing values non-missing records for
for consistency that variable (can use
linear
regression), another way is
, omission.
