Lesson 2.02j
2.02j Cleaning data and missing values Quiz: OCR Maths, Unit 12
20 questions
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Lesson 2.02j, Cleaning data and missing values: 20 multiple choice questions for the OCR Maths (H240), Unit 12: Data Presentation and Interpretation, written with Revision Ninja.
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The 20 questions
-
Which formula gives the lower outlier boundary using interquartile range?
- Q1 - 1.5 × SD
- Q1 - 1.5 × IQR
- Q3 - 1.5 × IQR
- Q1 - 2 × IQR
-
Which formula gives the upper outlier boundary using interquartile range?
- Q3 + 1.5 × IQR
- Q3 + 1.5 × SD
- Q1 + 1.5 × IQR
- Q3 + 2 × IQR
-
Which formula gives the upper outlier boundary using standard deviation?
- Mean + 1.5 × SD
- Median + 2 × SD
- Mean + 3 × SD
- Mean + 2 × SD
-
Which formula gives the lower outlier boundary using standard deviation?
- Mean - 3 × SD
- Mean - 1.5 × SD
- Median - 2 × SD
- Mean - 2 × SD
-
If Q1 is 10 and Q3 is 20, what is the lower outlier boundary?
- -10
- -5
- 5
- 0
-
If Q1 is 12 and Q3 is 24, what is the upper outlier boundary?
- 48
- 42
- 36
- 30
-
A dataset has mean 50 and standard deviation 8. What is the upper outlier threshold?
- 74
- 62
- 66
- 58
-
A dataset has mean 40 and standard deviation 5. What is the lower outlier threshold?
- 30
- 25
- 20
- 35
-
What term describes the process of removing or correcting erroneous data values?
- Data cleaning
- Data extrapolation
- Data regression
- Data sampling
-
What is an extreme data value that differs significantly from other observations called?
- Outlier
- Parameter
- Residual
- Variance
-
How should an obviously impossible recorded value, such as a negative height, be handled?
- Double the value
- Keep unchanged
- Remove or correct
- Replace with zero
-
Why are median and IQR preferred over mean and standard deviation for skewed data?
- Always give zero
- Resistant to outliers
- Ignore middle values
- Easier to calculate
-
In a dataset with Q1 = 10 and Q3 = 18, is 32 considered an outlier?
- Cannot be determined
- Yes, below threshold
- Yes, above threshold
- No, within limit
-
What is a common method for handling a single missing numerical value in cleaning?
- Deleting entire dataset
- Mean imputation
- Setting to infinity
- Linear regression
-
If a high upper outlier is removed from a dataset, what happens to the mean?
- Increases
- Decreases
- Becomes zero
- Stays the same
-
How does removing an extreme outlier affect the standard deviation of a dataset?
- It becomes negative
- It increases
- It stays unchanged
- It decreases
-
What happens to the median when the maximum outlier is removed from a dataset?
- Shifts slightly lower
- Increases significantly
- Stays strictly identical
- Doubles in value
-
For mean 100 and standard deviation 15, is 135 considered an outlier?
- Yes, above boundary
- Yes, below boundary
- No, below boundary
- No, on the mean
-
Which statistical diagram explicitly shows outliers as individual points beyond its whiskers?
- Pie chart
- Box plot
- Cumulative frequency
- Histogram
-
Given Q1 = 5 and Q3 = 8, what is the maximum non-outlier value threshold?
- 14.0
- 13.5
- 12.5
- 11.0
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