Page 1 of 48
2026/ 2027 C207 OA MOST TESTED Exam Questions WITH VERIFIED &
Correct Answers GRADED TO PASS!!!
Data doesn't follow pre-defined formats. Usually gets structured by a "theme
analysis"
i.e., blocks of freeform text, audio, video
Continuous Data
Data that can take any value (within a set range)
i.e., 3.14159, -189,115.2
a thermometer reads 66.5 degrees
Interval Data (data measuring levels)
data is ordered at equal intervals apart and "0" doesn't mean absence of data, just
another data point
a type of continuous data
i.e. date, time, degrees
Ratio Data (data measuring levels)
0 actually means nothing, not just a data point
a type of continuous data
i.e. money, height weight
Discrete Data
Data that can only take on whole values and has clear boundaries
Page 1 of 48
, Page 2 of 48
i.e. 4, 7, 8 in a preset range of 1-100
Ordinal data (data measuring levels)
data is ordered based on quality
a type of discrete data
i.e. in blackbelt data, level "3" is higher quality than "1"
gold, silver, and bronze medals
Nominal / Categorical Data (data measuring levels)
data is assigned a category/label for identification and grouping purposes
a type of discrete data
i.e. males are assigned "0" and females "1"
potential quality errors: categories can be misspelled
Attribute Data
Data that shows whether a result meets a requirement or not (yes/no, pass/fail).
Davenport-Kim Three-Stage Model
1. Frame the problem - recognize problem and review previous findings.
2. Solve the problem - modeling, collection, analysis
3. Communicate results - tailor to audience, use visuals, show results.
Reliability of Data
Page 2 of 48
, Page 3 of 48
data that is consistent (but not necessarily accurate)
i.e. a thermometer reads 20, 21, 21, 20, 20, 19, 19, 21, 20, 19
a test given to a student consistently shows similar scores
Validity of Data
data that is accurate
requires sample selection to be adequate size and random.
i.e. a thermometer consistently reads from 20-25 F but the water isn't even frozen
(not valid)
Data Error Types
Omission - data being left out, missed, forgotten. sorting in spreadsheet can help to
identify
Out of Range - data that doesn't fit the expected, viable range. sorting in
spreadsheet can help to identify outliers.
Entry/input errors - typos, miscommunications, illegible handwriting
Systematic Error
error will cause other errors until fixed
i.e. a tire pressure sensor breaks and stops functioning, resulting in omission errors
until fixed
a scale is calibrated prior to being used in order to reduce systemic error
Page 3 of 48
, Page 4 of 48
Random Error / Unpredictable Error
error that does not consistently repeat due to system flaw and therefore doesn't
need fix/adjustment. aka its "self-fixing".
minimize effects by increasing sample size
i.e. a tire pressure sensor records an outlier / out-of-range caused by going over a
speed bump at high speed
True Score Theory
Observed Score (raw data score) = true score + random error score + systematic
error
in absence of systematic error, it's just true score + random error
Measurement Bias
data doesn't represent the study group because of:
1. sample isn't random enough
2. sample isn't big enough
3. sample wasn't inclusive enough, or was too inclusive, to represent study group
i.e. a survey on favorite foods was sent to all renters in a city (didn't include
homeowners so not a "Truly Representative Sample")
Simple indexing
Common analytic measure to improve performance. Compares current data with
data during a base period.
(Price / Price during "Base Period") x 100
Page 4 of 48
2026/ 2027 C207 OA MOST TESTED Exam Questions WITH VERIFIED &
Correct Answers GRADED TO PASS!!!
Data doesn't follow pre-defined formats. Usually gets structured by a "theme
analysis"
i.e., blocks of freeform text, audio, video
Continuous Data
Data that can take any value (within a set range)
i.e., 3.14159, -189,115.2
a thermometer reads 66.5 degrees
Interval Data (data measuring levels)
data is ordered at equal intervals apart and "0" doesn't mean absence of data, just
another data point
a type of continuous data
i.e. date, time, degrees
Ratio Data (data measuring levels)
0 actually means nothing, not just a data point
a type of continuous data
i.e. money, height weight
Discrete Data
Data that can only take on whole values and has clear boundaries
Page 1 of 48
, Page 2 of 48
i.e. 4, 7, 8 in a preset range of 1-100
Ordinal data (data measuring levels)
data is ordered based on quality
a type of discrete data
i.e. in blackbelt data, level "3" is higher quality than "1"
gold, silver, and bronze medals
Nominal / Categorical Data (data measuring levels)
data is assigned a category/label for identification and grouping purposes
a type of discrete data
i.e. males are assigned "0" and females "1"
potential quality errors: categories can be misspelled
Attribute Data
Data that shows whether a result meets a requirement or not (yes/no, pass/fail).
Davenport-Kim Three-Stage Model
1. Frame the problem - recognize problem and review previous findings.
2. Solve the problem - modeling, collection, analysis
3. Communicate results - tailor to audience, use visuals, show results.
Reliability of Data
Page 2 of 48
, Page 3 of 48
data that is consistent (but not necessarily accurate)
i.e. a thermometer reads 20, 21, 21, 20, 20, 19, 19, 21, 20, 19
a test given to a student consistently shows similar scores
Validity of Data
data that is accurate
requires sample selection to be adequate size and random.
i.e. a thermometer consistently reads from 20-25 F but the water isn't even frozen
(not valid)
Data Error Types
Omission - data being left out, missed, forgotten. sorting in spreadsheet can help to
identify
Out of Range - data that doesn't fit the expected, viable range. sorting in
spreadsheet can help to identify outliers.
Entry/input errors - typos, miscommunications, illegible handwriting
Systematic Error
error will cause other errors until fixed
i.e. a tire pressure sensor breaks and stops functioning, resulting in omission errors
until fixed
a scale is calibrated prior to being used in order to reduce systemic error
Page 3 of 48
, Page 4 of 48
Random Error / Unpredictable Error
error that does not consistently repeat due to system flaw and therefore doesn't
need fix/adjustment. aka its "self-fixing".
minimize effects by increasing sample size
i.e. a tire pressure sensor records an outlier / out-of-range caused by going over a
speed bump at high speed
True Score Theory
Observed Score (raw data score) = true score + random error score + systematic
error
in absence of systematic error, it's just true score + random error
Measurement Bias
data doesn't represent the study group because of:
1. sample isn't random enough
2. sample isn't big enough
3. sample wasn't inclusive enough, or was too inclusive, to represent study group
i.e. a survey on favorite foods was sent to all renters in a city (didn't include
homeowners so not a "Truly Representative Sample")
Simple indexing
Common analytic measure to improve performance. Compares current data with
data during a base period.
(Price / Price during "Base Period") x 100
Page 4 of 48
