This chapter is also basic. It is about some common summary statistics, relationships between ratios, percentages, and proportions, and data types.

I am not going to cover the summary statistics here since I am sure you already know what is averages, medians, ranges, root mean square deviations, and standard deviations.

The relationship between ratios, percentages, and proportions is interesting. However, it does not affect much of our daily work, I believe. If the units of measurement for the numerator are different from the units of measurement for the denominator, it is called ratios. If they are the same, it is called percentages. If the denominator limits or restricts the numerator in some way, such as the total sale of a region/ total sale of the whole organisation, it is called proportions. That is why proportions must always fall between 0 and 1.

Finally, the author introduces the concept of data types which I think may be useful in future chapters:

Nominal Data

Numbers as labels

Ordinal Data

Numbers represent the order of items or categories

Interval Scale Data

The number can fall below zero, such as degrees

Ratio Scale Data

The number cannot fall below zero

For Nominal Data and Ordinal Data, calculating the average is meaningless since they do not represent distance. This serves as an example of why knowing data types is useful in analysis.