# Glossary


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(Eg. "Genetic, Hereditary, DNA ...") (Eg. "Relating to genes or heredity") The infamous double helix https://bio.libretexts.org/ CC-BY-SA; Delmar Larsen
Glossary Entries

Word(s)

Definition

Statistical analysis, statistical analyses

Procedures to organize and interpret numerical information

CC-BY Michelle Oja
Statistic The results of statistical analyses       CC-BY Michelle Oja
Independent Variable, IV  The variable that the researcher thinks is the cause of the effect (the DV).  The IV is sometimes also called a "predictor" or "predicting variable".       CC-BY Michelle Oja
Dependent Variable, DV

The variable that you think is the effect (the thing that the IV changes).  The DV is the outcome variable, the thing that you want to improve.

CC-BY Michelle Oja
Sample, samples People who participate in a study; the smaller group that the data is gathered from.       CC-BY Michelle Oja
Population The biggest group that your sample can represent.       CC-BY Michelle Oja
Ratio True numerical scale of measurement; type of variable that is measured, and zero means that there is none of it.       CC-BY Michelle Oja
Interval Created numerical scale of measurement; type of variable that is measured, and the intervals between each measurement are equal (but zero does not mean the absence of the measured item).       CC-BY Michelle Oja
Ordinal  Scale of measurement in which levels have an order; a type of variable that can be put in numerical order. The variables are in ranks (first, second, third, etc.).       CC-BY Michelle Oja
Nominal Scale of measurement that names the variable's levels; type of variable that has a quality or name, but not a number that means something.         CC-BY Michelle Oja
Quantitative variable, quantitative variables Type of variable that is measured with some sort of scale that uses numbers that measure something.       CC-BY Michelle Oja
Qualitative variable, qualitative variables Type of variable that has different values to represent different categories or kinds  This is the same as the nominal scale of measurement.       CC-BY Michelle Oja
Frequency Table Table showing each score in the “x” column, and how many people earned that score in the “f” column.  The “x” stands in for whatever the score is, and the “f” stands for frequency.       CC-BY Michelle Oja
Outlier An extreme score, a score that seems much higher or much lower than most of the other scores (There is a technical way to calculate whether a score is an outlier or not, but you don't need to know it.)       CC-BY Michelle Oja
Skew, skewed distribution A distribution in which many scores are bunched up to one side, and there are only a few scores on the other side.       CC-BY Michelle Oja
Positive skew The scores are bunched to the left, and the thin tail is pointing to the right. Positive skew is shown on the right panel. Rodolfo Hermans (Godot), CC BY-SA 3.0 via Wikimedia Commons CC-BY Michelle Oja
Negative skew The scores are bunched to the right, and the thin tail is pointing to the left. Negative skew is shown on the left panel. Rodolfo Hermans (Godot), CC BY-SA 3.0 via Wikimedia Commons CC-BY Michelle Oja
Kurtosis A measure of the “tailedness” of the distribution of data (how wide or broad the distribution is) Example of different types of kurtosis. Larry Green, CC-BY CC-BY Michelle Oja
Leptokurtic A tall and narrow distribution of data. The tallest (blue) line is a leptokurtic shape. Larry Green, CC-BY CC-BY Michelle Oja
Platykurtic A wide and flat distribution of data. The lowest (red) line is a platykurtic shape. Larry Green, CC-BY CC-BY Michelle Oja
Mesokurtic A medium, bell-sharped distribution of data. The middle (black) line is a mesokurtic shape. Larry Green, CC-BY CC-BY Michelle Oja
Frequency Distribution A distribution of data showing a count of frequency (how many) for each score or data point.       CC-BY Michelle Oja
Range The difference between the highest score and the lowest score in a distribution of quantitative data.       CC-BY Michelle Oja
Robust A term used by statisticians to mean resilient or resistant to       CC-BY-NC-SA Foster et al.
Descriptive Statistics Used to describe or summarize the data from the sample.       CC-BY Michelle Oja
Inferential Statistics Used to make generalizations from the sample data to the population of interest.       CC-BY Michelle Oja
Parameter Statistic describing characteristics of the population (usually mean and standard deviation of the population)       CC-BY Michelle Oja
Non-Parametric Analysis, non-parametric analyses Statistical analyses using ranked data; used when data sets are not normally distributed or with ranked data       CC-BY Michelle Oja
Research Hypothesis A prediction of how groups are related.  When comparing means, a complete research hypothesis includes:
1. The name of the groups being compared.  This is sometimes considered the IV.
2. What was measured.  This is the DV.
3. Which group are we predicting will have the higher mean.
CC-BY Michelle Oja
Null Hypothesis A prediction that nothing is going on.  The null hypothesis is always:

1.  There is no difference between the groups’ means

OR

2.  There is no relationship between the variables.

CC-BY Michelle Oja
Absolute value Any number converted to a positive value     https://crumplab.github.io/statistic...ibingData.html CC-BY-SA Mattew J. C. Crump
Main Effect Any statistically significant differences between the levels of one independent variable in a factorial design.       CC-BY-SA Mattew J. C. Crump
Interaction, interaction effect How the levels of two or more IVs jointly affect a DV; when one IV interacts with the other IV to affect the DV.       CC-BY Michelle Oja
Positive Correlation When two quantitative variables vary together in the same direction; when one increases, the other one also increases (and when one decreases, the other also decreases)       CC-BY Michelle Oja
Negative Correlation When two quantitative variables vary in opposite directions; when one variable increases, the other variable decreases.       CC-BY Michelle Oja
Binary variable, binary A binary variable is a variable that only has two options (yes or no).  Binary variables can be considered quantitative or qualitative.         CC-BY- Michelle Oja
Dichotomous variable, dichotomous A dichotomous variable is a variable that only has two options (yes or no).  Binary variables can be considered quantitative or qualitative.         CC-BY- Michelle Oja