Description of the Scientific Process: Glossary of Terms
Glossary of Terms
Abstract – In a paper, a short summary of the full paper.
Alternative hypothesis – In statistics, the hypothesis that one mean is larger than, smaller than, or unequal to another mean with statistical significance.
Analysis of variance (ANOVA) – In statistics, a way to test multiple means against each other for statistical significance.
Bar / column chart – A chart with classes of data and their magnitudes.
Binomial data – In statistics, data that is an either/or proposition, for example, 0 or 1, or yes or no.
Chi-square (Χ2) test – In statistics, a test to determine whether quantities of different classes match expected quantities.
Confidence interval – In statistics, the upper and lower bounds of the estimation of the population mean, given the sample data.
Controlled experiment – An experiment in which one sample is set up as a control, and other samples are set up to vary one or more independent variables.
Degrees of freedom – In statistics, the number of values in the final calculation of statistic that are free to vary.
Dependent variable – The variable that is measured as the result of the experimental effect.
Discussion – In a paper, the section that is used to describe the impact of results and speculate about their meaning.
Error bar – On a graph, the upper and lower bounds of a confidence interval.
Experiment – A systematic approach designed to test a hypothesis.
Experimental bias – An undesired effect leftover from accidents in the experiment.
Experimental sample / treatment sample – In an experiment, the sample(s) that has (have) variables different from the control sample.
Figure – In a paper, poster, or presentation, a chart, photograph, drawing, map, etc.
Histogram – A special kind of bar / column chart that compares the frequencies of ranges of a variable.
Hypothesis – A testable idea that could explain an observed phenomenon.
Hypothesis test – In statistics, a test to determine whether two estimated means are different from each other with statistical significance.
Independent variable – A variable that is altered by the experimenter or otherwise varied across treatments.
Introduction – In a paper, the section that describes the system and introduces the problem addressed.
Literature citation – In a paper, a callout to previously produced work used to support a point.
Margin of error – In statistics, the value added to and subtracted from the sample proportion to generate the upper and lower bounds of the confidence interval.
Materials and methods – In a paper, the section that describes sources for materials and the parameters of the experiments.
Mean (arithmetic) – In statistics, the sum of all variable values for individuals in a sample divided by the number of individuals in the sample.
Median – In statistics, the value of a variable for one individual separating the upper half of the distribution from the lower half of the distribution.
Mode – In statistics, the most common value for a variable in a sample.
Natural experiment – An experiment comparing existing natural samples using natural variation to determine independent and dependent variables.
Noise – Random variation in a value.
Null hypothesis – In statistics, the hypothesis that two sample means are not different from each other with statistical significance.
Outlier – A value for an individual’s variable that is unusually much larger or smaller than the mean or otherwise appears to be non-normal.
p-value – In statistics, the probability of getting a test statistic result at least as extreme as what was observed, assuming that the null hypothesis is true.
Pearson coefficient – A measure of the linear correlation between two variables for a sample.
Pilot experiment – A miniature experiment used to test the viability of and potential pitfalls for a real experiment.
Plagiarism – Unattributed use of another’s text or other materials.
Probability of success – In a binomial variable for a population, the likelihood that an individual will have a particular value.
Results – In a paper, the section that describes what the experimenter(s) found.
Sample – A group of individuals that were all exposed to the same treatment.
Sample size – The number of individuals in a sample.
Scatter plot – A chart in which individuals are organized for two variables, one of which varies on the x-axis, and the other of which varies on the y-axis.
Sample proportion – In statistics, the proportion of individuals that have a certain value for a binomial variable.
Sample Variance – In statistics, a measure of the variation in a variable across the sample. In square units of the original variable.
Signal – The non-random variation in values that conveys useful information.
Standard deviation – In statistics, a measure of the variation in a variable across the population. In the same units of the original variable.
Standard error - In statistics, a measure of the variation in a variable across the sample. In the same units of the original variable.
Statistical significance – In statistics, having a low probability of randomly reproducing at least as extreme a result as found within the data.
System – The organism, mineral, interaction, etc., that you are working on in your research.
Treatment – A set of conditions under which an experiment is being performed.
Variation – The difference or divergence within or among samples.