37.10 Writing carefully: Lexically ambiguous words
As noted in Sect. 37.1, writing carefully and precisely is incredibly important in science.
One aspect of writing well is using lexically ambiguous words carefully. Lexically ambiguous words have a different meaning in other scientific disciplines, or in their usual every-day use (Richardson et al. 2013; Dunn et al. 2016). If you are unsure of the definitions used in this book, make use of the Glossary (Appendix G).
Here are some lexically ambiguous words to be wary of:
- Average: In statistics and research, ‘average’ can refers to any way of measuring the typical value (Sect. 13.2), including the mean and the median, but also other measures too. Use the specific word ‘mean’ or ‘median’ if that is what you actually intend!
- Confidence: In statistics and research, the word ‘confidence’ is usually used in the phrase ‘confidence interval,’ where it has a specific meaning (Sect. 21.2).
- Comparison: In statistics and research, a ‘comparison’ (Sect. 2.3.3) is when the sample and population can be separated into two or more groups that are either treated differently (e.g., one group is given a placebo, and one a treatment) or are fundamentally different (e.g., aged under 40, or aged 40 or over).
- Control: In statistics and research, a ‘control’ refers to a specific situation, and is helpful for maximising internal vaidity (Def. 7.6).
- Correlation: In statistics and research, correlation describes the relationship between two quantitative variables (Sect. 34.1).
- Estimate: In statistics and research, ‘estimating’ usually means to find a sample value (i.e., to make a calculation) to estimate an unknown population parameter, rather than the colloquial use where it often means to take a guess (Sect. 2.5).
- Experiment: In statistics and research, an experiment is a specific type of research study (Sect. 3.4). Use the word ‘study’ to talk about experimental and observational studies more generally.
- Graph: In statistics and research, a ‘graph’ is used to summarise data (Chap. 12).
- Independent: This words has many uses in statistics and research, in science, and in general use.
We use the word ‘independent’ in this book to refer to events that do not impact each other in a probabilistic sense (Sect. 16.5).
- Intervention: In statistics and research, an ‘intervention’ (Sect. 2.3.4) is how the researchers manipulate the comparison or connection.
- Normal: In statistics and research, ‘normal’ usually refers to the ‘normal distribution’ (Chap. 17.3). If this is not the meaning you intend to convey, consider using the word ‘usual.’
- Odds: In statistics and research, ‘odds’ has a specific meaning (Sect. 14.2) and is different that probability, whereas ‘probability’ and ‘odds’ are often used interchangeably in general usage.
- Population: In statistics and research, the ‘population’ refers to a larger group of interest (Sect. 2.3.1), whereas in general use ‘population’ usualy refers to groups of people.
- Random: In statistics and research, ‘random’ has a specific meaning, but in general usage it often means ‘haphazard.’
- Regression: In statistics and research, ‘regression’ refers to the mathematical relationship between two quantitative variables (Sect. 35).
- Sample: In statistics and research, we say (for example) that we ‘have taken one sample of 30 fungi’ (Sect. 5.1); in some disciplines, this could be described as ‘taking 30 samples.’
- Significant: This is perhaps the most mis-used word in scientific writing. In statistics and research, ‘significance’ is usually understood to refer to ‘statistical significance’ (Sect. 28.6).
If this is not the meaning you intend to convey, consider using the word ‘substantial.’
- Variable: In statistics and research, a ‘variable’ is something that can vary from individual to individual (Def. 2.11).
Furthermore, some symbols may have different meanings in research and statistics than in some other scientific disiplines; again, care is needed when using these symbols:
- \(\beta\): In this book, \(\beta\) refers to the regression parameters (Sect. 35.3).
- \(\rho\): In this book, \(\rho\) refers to the population correlation coefficient (Sect. 34.1).
- \(\pm\): In this book, the symbol \(\pm\) is used for confidence intervals to describe a range of values in which the population parameter probably lies (Sect. 21).