The BASK separates what you measure with from how you prepare the data. Two lists, and the exam tests which term sits on which.
Basic statistics and measurement
The BASK's basic statistics and measurement key concept covers descriptive statistics, correlation, reliability and validity.
- Descriptive statistics: summary measures such as the mean and the median that describe a data set.
- Correlation: the relationship between two variables.
- Reliability: consistency of measurement.
- Validity: whether a measure captures what it intends to capture.
When a workforce has a handful of very long-serving employees pulling the average above typical tenure, reporting both the mean and the median is descriptive statistics - not correlation, not reliability, not validity.
The lists it is confused with
- Bar charts, line graphs, scatterplots and histograms are the separate key concept on interpretation of graphs and charts.
- Data cleansing, data mining, visualization, big data analysis, statistical analysis, predictive analysis and data and algorithm quality are the data analysis techniques list.
- Balance sheets, budgets, cash flow statements and overhead are Business Acumen financial analysis terms and do not belong in Analytical Aptitude at all.
Data cleansing
Data cleansing is the technique for correcting duplicate and inconsistent records - duplicated employee IDs, job titles entered inconsistently. It is the answer whenever the problem is the quality of the underlying records.
- Predictive analysis forecasts future outcomes and would inherit the same errors.
- Big data analysis concerns the scale of data, not its quality.
- Data visualization presents data graphically without fixing the records beneath it.
Carry this in: if the stem describes a *property of a measure*, you are in basic statistics and measurement; if it describes *work done to the data*, you are in data analysis techniques.