BUSINESS STATISTICS FOR
CONTEMPORARY DECISION MAKING
COMPREHENSIVE TEST PAPER QUESTIONS
AND SOLUTIONS GRADED APLUS
●● Choosing the right test
Answer: ANOVA vs Regression vs Chi-Square
●● Correlation vs Causation
Answer: OA loves to see if you'll say 'causes' instead of 'associated with'
●● P-Value interpretation
Answer: small p = reject the NULL (and vice versa)
●● Control Charts vs Histograms Vs Pareto
Answer: identifying the right chart from a description
●● Probability rules
Answer: AND= Multiply, OR= Add, Complement = 1-P(event)
●● Expected Value problems
,Answer: often hidden in word problems without explicitly saying
'Decision Tree'
●● Big Data
Answer: Both structured and unstructured data in such large volumes
that it's difficult to process
●● Data storage
Answer: Stored in data warehouses, generally cloud or server storage
●● Data mining
Answer: process of discovering patterns in large data sets
●● Types of data
Answer: Qualitative & Quantitative
●● Levels of measurement: NOIR
Answer: Nominal - no number, no sequence; Ordinal - no number, yes
sequence; Interval - number, zero is a placeholder; Ratio - number, zero
is the absence of any
●● Ordinal example
Answer: rental car category such as compact, economy and luxury
, ●● Interval example
Answer: Temperatures such as 0 degrees-107 degrees
●● Ratio example
Answer: pricing where zero can mean absence of none and increases
●● Nominal Data
Answer: Return or not
●● Ratio Data
Answer: Cost/money
●● Reliable
Answer: meaning consistent and repeatable, a measurement of the
instrument (test)
●● Valid
Answer: meaning the measurement intended and complicit. Does your
test scores represent your ability
●● Data Quality
Answer: range, spelling, omission issues
CONTEMPORARY DECISION MAKING
COMPREHENSIVE TEST PAPER QUESTIONS
AND SOLUTIONS GRADED APLUS
●● Choosing the right test
Answer: ANOVA vs Regression vs Chi-Square
●● Correlation vs Causation
Answer: OA loves to see if you'll say 'causes' instead of 'associated with'
●● P-Value interpretation
Answer: small p = reject the NULL (and vice versa)
●● Control Charts vs Histograms Vs Pareto
Answer: identifying the right chart from a description
●● Probability rules
Answer: AND= Multiply, OR= Add, Complement = 1-P(event)
●● Expected Value problems
,Answer: often hidden in word problems without explicitly saying
'Decision Tree'
●● Big Data
Answer: Both structured and unstructured data in such large volumes
that it's difficult to process
●● Data storage
Answer: Stored in data warehouses, generally cloud or server storage
●● Data mining
Answer: process of discovering patterns in large data sets
●● Types of data
Answer: Qualitative & Quantitative
●● Levels of measurement: NOIR
Answer: Nominal - no number, no sequence; Ordinal - no number, yes
sequence; Interval - number, zero is a placeholder; Ratio - number, zero
is the absence of any
●● Ordinal example
Answer: rental car category such as compact, economy and luxury
, ●● Interval example
Answer: Temperatures such as 0 degrees-107 degrees
●● Ratio example
Answer: pricing where zero can mean absence of none and increases
●● Nominal Data
Answer: Return or not
●● Ratio Data
Answer: Cost/money
●● Reliable
Answer: meaning consistent and repeatable, a measurement of the
instrument (test)
●● Valid
Answer: meaning the measurement intended and complicit. Does your
test scores represent your ability
●● Data Quality
Answer: range, spelling, omission issues
