4/15/25, 11:08
AM
Mid Term - BUAL - 5380 - Managerial
Decision - Exam 1 Study Guide: Key
Statistical Concepts exam questions and
answers verified
Practice questions for this set
Learn 1/7 Study using Learn
Numerical (e.g. height, income).
Select the correct term
1/
9
, 4/15/25, 11:08
AM 1Quantitative 2Descriptive
3Qualitative 4Categorical (Qualitative)
Don't know?
Terms in this set (89)
Define problem collect data analyze data interpret
Decision-making process make informed decision
Creating simplified representations (models) to
Modelling process describe, explain, or predict real-life phenomena.
Population Whole group you want info about.
A smaller group taken from the
Sample population for analysis.
You use sample data to make inferences
Relation about the population.
Categorical (Qualitative) Labels or names (e.g. gender,
brand). Quantitative Numerical (e.g. height, income).
Nominal Categories with no order (e.g. colors).
Ordinal Categories with a meaningful order (e.g. rankings).
Cross-sectional Collected at one point in time.
Time-Series Collected over multiple time points.
Discrete Countable values (e.g. # of books).
Continuous Infinite values within a range (e.g. weight).
Frequency Table Table showing how often values
occur. Mean Average.
Median Middle value.
Mode Most frequent value.
2/
9
AM
Mid Term - BUAL - 5380 - Managerial
Decision - Exam 1 Study Guide: Key
Statistical Concepts exam questions and
answers verified
Practice questions for this set
Learn 1/7 Study using Learn
Numerical (e.g. height, income).
Select the correct term
1/
9
, 4/15/25, 11:08
AM 1Quantitative 2Descriptive
3Qualitative 4Categorical (Qualitative)
Don't know?
Terms in this set (89)
Define problem collect data analyze data interpret
Decision-making process make informed decision
Creating simplified representations (models) to
Modelling process describe, explain, or predict real-life phenomena.
Population Whole group you want info about.
A smaller group taken from the
Sample population for analysis.
You use sample data to make inferences
Relation about the population.
Categorical (Qualitative) Labels or names (e.g. gender,
brand). Quantitative Numerical (e.g. height, income).
Nominal Categories with no order (e.g. colors).
Ordinal Categories with a meaningful order (e.g. rankings).
Cross-sectional Collected at one point in time.
Time-Series Collected over multiple time points.
Discrete Countable values (e.g. # of books).
Continuous Infinite values within a range (e.g. weight).
Frequency Table Table showing how often values
occur. Mean Average.
Median Middle value.
Mode Most frequent value.
2/
9
