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Glossary
association
In statistics we say that there is an association between two variables if the two variables are statistically related to each other; if the value of one of the variables can be used to estimate the value of the other.
bell-shaped distribution
A distribution whose dot plot or histogram takes the form of a bell with most of the data clustered near the center and fewer points farther from the center.
bimodal distribution
A distribution with two very common data values seen in a dot plot or histogram as distinct peaks.
categorical data
Categorical data are data where the values are categories. For example, the breeds of 10 di erent dogs are categorical data. Another example is the colors of 100 di erent  owers.
categorical variable
A variable that takes on values which can be divided into groups or categories. For example, color is a categorical variable which can take on the values, red, blue, green, etc.
causal relationship
Arelationship is one in which a change in one of the variables causes a change in the other variable.
constraint
An limitation on the possible values of variables in a model, often expressed by an equation or inequality or by specifying that the value must be an integer. For example, distance above the ground  , in meters, might be constrained to be non-negative, expressed by    .
correlation coe cient
A number between -1 and 1 that describes the strength and direction of a linear association between two numerical variables. The sign of the correlation coe cient is the same as the sign of the slope of the best  t line. The closer the correlation coe cient is to 0, the weaker the linear relationship. When the correlation coe cient is closer to 1 or -1, the linear model  ts the data better.
distribution
For a numerical or categorical data set, the distribution tells you how many of each value or each category there are in the data set.
elimination
A method of solving a system of two equations in two variables where you add or subtract a multiple of one equation to another in order to get an equation with only one of the variables (thus eliminating the other variable).
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