Statistical Measure for Disease Case Calculation
Use the mean (A) to calculate the average number of disease cases over different time periods when analyzing 14 different case numbers.
Rationale for Mean Selection
The mean is the appropriate measure of central tendency for calculating the average number of cases across different time periods in epidemiological surveillance. 1 This aligns with standard epidemiological practice where disease case counts are routinely reported and analyzed using mean values to establish baseline trends and detect outbreaks. 1
Why Other Options Are Inappropriate
Mode (B) - Not Suitable
- Mode identifies the most frequently occurring value in a dataset, which provides no meaningful information about average disease burden across time periods 2
- In epidemiological surveillance with 14 different case numbers, the mode would only tell you which specific case count appeared most often, not the typical disease burden 2
Median (C) - Limited Application Here
- While median is excellent for skewed distributions like incubation periods, it is less informative for calculating average case counts across time periods 3, 2
- Median would be appropriate if the question asked about central tendency with extreme outliers, but the question specifically asks to "calculate" average cases 3
Range (D) - Measures Dispersion, Not Central Tendency
- Range only describes variability (maximum minus minimum) and provides no information about average case numbers 2, 4
- Range is a measure of dispersion, not a measure of central tendency needed to answer "how many cases" on average 2
Epidemiological Context
- Disease surveillance systems routinely use mean case counts to establish baseline rates and compare across time periods 1
- The CDC's Morbidity and Mortality Weekly Report consistently reports mean values when comparing provisional case totals to historical data 1
- Mean calculations allow epidemiologists to detect deviations from expected case numbers, which is fundamental for outbreak detection 1