Correlation
Explanatory
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Chi-square is a statistic used to assess the degree of the relationship and degree of association between two nominal variables
Degree and direction of relationship between two or more variables is known as correlation.
Correlation is defined as the degree of relationship between two or more variables. It is also called the simple correlation. The degree of relationship between two or more variables is called multi correlation. when two or more variables are said to be higjly correlated it means that they have a strong relationship such that a given rise or fall in one variable will lead to a direct change in the other variable or variables. good examples of highly correlated variables are price and quantity, wage rate and out put, tax and income.
what is the relationship between complexity and the cephilization of a sponge?
Degree the number of entity types that participate in a relationship.
A correlation of 0.20 is somewhat low, meaning that the degree of linear relationship measured between the two variables involved is low. However, such a degree of relationship would not be ignored in many fields of science where relationships are difficult to detect. Correlation is rarely if ever put in terms of percentage.
a linear relationship is characterized by the form y=mx+b and a quadratic relationship is characterized by the form y=x^2+bx+c. Graphically represented, a linear equation forms a line and a quadratic will appear as a parabola.
The principal advantage over casual comparative or experimental designs is that they enable researchers to analyze the relationships among a large number of variables in a single study. Another advantage of correlational designs is that they provide information concerning the degree of the relationship between the variables being studied. Correlational research designs are used for two major purposes: (1) to explore casual relationship between variables and (2) to predict scores on one variable from research participants' scores on other variables.
mutualism
Coefficient of multiple determination