1.2.1 Basic descriptive statistics

Descriptive analysis is the process of summarising data and generally involves characterising and visualising your dataset. Depending on the nature of the data, you may only need to undertake a descriptive analysis before reporting your findings. The approach to descriptive analysis varies depending on whether the data is categorical or numerical.

1.2.1.1 Categorical variables

Descriptive statistics for categorical variables include counts (frequencies) and proportions (relative frequencies). Percentages are obtained by multiplying proportions by 100.

AMR data is often presented as basic descriptive statistics in sentences in a report, in a frequency table, or in a visual format using a pie chart or a bar chart. An example of using text is in reporting the percentage of isolates that were resistant:

‘A large number of MRSA isolates showed resistance to levofloxacin (83.9%), ciprofloxacin (83%), erythromycin (77.7%), and clindamycin (72.3%).’

(Kot et al., 2020)

Activity 3: Approaches to presenting information

Timing: Allow about 10 minutes

Figure 1 and Table 3 displays data from the Third Australian Report on Antimicrobial Use and Resistance in Human Health (AURA), 2019. Table 3 is a frequency table showing the percentage of prescribed antibiotics, and Figure 1 shows the same data in a bar chart.

Table 3 The ten most commonly dispensed antibiotics under the Pharmaceutical Benefits Scheme/Repatriation Pharmaceutical Benefits Scheme, by percentage of all antibiotic prescriptions, 2017 (ACSQHC, 2019)
Antimicrobial classPercentage (%)
Cefalexin20.1
Amoxicillin19.7
Amoxicillin-clavulanic acid17.5
Doxycycline8.0
Roxithromycin5.1
Trimethoprim3.4
Flucloxacillin2.9
Clarithromycin2.9
Metronidazole2.5
Erythromycin2.1
Total100
Described image
Figure 1 The ten most commonly dispensed antibiotics under the Pharmaceutical Benefits Scheme/Repatriation Pharmaceutical Benefits Scheme, by percentage of all antibiotic prescriptions, 2017 (ACSQHC, 2019)
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An ordered list of the ten most commonly disposed antibiotics under the Pharmaceutical Benefits Scheme, by percentage, shown as a bar chart (RHS, B).

Figure 1 The ten most commonly dispensed antibiotics under the Pharmaceutical Benefits Scheme/Repatriation Pharmaceutical Benefits ...

Which type of data display (Table 3 or Figure 1) do you think most effectively conveys information about the most and least commonly dispensed antibiotics in Australia in 2017?

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Answer

While tables can summarise and display data to great effect, in this example, the bar chart (Figure 1) demonstrates a superior approach to presenting the data. When looking at the bar chart, it can be rapidly determined that there is a pronounced difference between the most commonly prescribed and least prescribed antimicrobials.

Do you agree that your brain needs to work harder to get the same information from the table?

1.2.1.2 Quantitative variables

Descriptive statistics for quantitative (numerical) variables (continuous or discrete) include measures of central tendency and measures of spread. Summary statistics include the mean, standard deviation, median, minimum and maximum. Summary statistics can be calculated to summarise quantitative variables in a dataset.

Descriptive statistics for quantitative variables can be reported as text, as a summary table, or using a histogram or box-and-whisker plot. We’ll be discussing histograms and box-and-whisker plots later in this module.

1.2 Review of different approaches to data analysis

1.2.2 Plotting variability in data