Adding visual explanations to text can help to clarify its meaning and help readers to understand what the author wants to convey. Visual aids often help to explain complex ideas. In addition, visual cues can help people to remember information longer. This is why information is often translated into visual aids to accompany textual information or to view as a standalone. From ‘how to’ manuals to DNA sequencing, visual explanations can add value to almost any subject.

Statistics

In a big data world, statistics are a driving force in our lives. They are simply the collection and categorization of data. This gathering and compilation of data can inform us about the cost of living, how many people live in a given city, who uses public transportation, and so on. Statistics are often collected and used to determine how money is spent by the government; how many representatives an area can have in a democratic government; how many park rangers are needed in a national park, for example. Statistics also influence individual decisions – which is the best car to buy; how many people in my area buy products like mine; what is the cost of housing in my area; and what is the most popular color for spring fashion this year. Statistics can help to formulate an argument for or against a policy or action. Mark Twain is often credited with the quote: ‘There are three kinds of lies. There are lies, damn lies, and statistics.’ While it is uncertain whether Twain was actually the person who coined this quote, its implication is clear: statistics can be manipulated to persuade, to misinform or to mislead.

Descriptive statistics report on the numbers collected. The Pew Research Center, for example, collects and reports on this type of statistic. A recent study stated that ‘[m]ost U.S. adults continue to support expanding solar panel farms (84%) and wind turbine farms (77%)’ (Kennedy and Spencer, 2021). The raw data (the number of people who said ‘yes’ or ‘no’) is converted into a percentage. The percentage may be extrapolated with a high degree of certainty to include the entire population if enough data was collected. In descriptive statistics, a small sample of the population can predict the opinions of the entire population, within a margin of error.