Bivariate Data and Scatter Plot Statistics PDF

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Bivariate Data and Scatter Plot Statistics...

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BIVARIATE DATA AND SCATTER PLOT Bivariate Data – consists of two (2) variables and can be either dependent or independent variable. Independent Variable – is the variable that can cause the dependent variable to change. Dependent Variable – is the variable that is influenced or affected by the independent variable. Scatter Plot - are diagrams that are used to show the degree and pattern of relationship between the two (2) sets of data. They are constructed on the XY Coordinate plane. Each data point on a scatter plot represents two (2) values. The abscissa of the point is a value of the independent variable, and the ordinate is a value of the dependent variable. Examples: Situation 1: You want to test a new dosage of drug that supposedly prevents sneezing in people allergic to flowers. Variable in the x-axis: new dosage of drug Variable in the y-axis: Sneezing Situation 2: A soap manufacturer wants to prove that a little amount of detergent can remove greater amount of stain. Variable in the x-axis: amount of detergent Variable in the y-axis: Amount of stain removed Patterns of Data in Scatter Plot  Linearity refers to whether a data pattern is linear (straight) or nonlinear (curved).  Slope refers to the direction of change in variable y when variable x gets bigger. If variable y also gets bigger, the slope is positive; but if variable y gets smaller, the slope is negative.  Strength refers to the degree of “scatter” in the plot. If the dots are widely spread, the relationship between variables is weak. If the dots are concentrated around a line, the relationship is strong.

linear positive trend or slope weak

linear no slope weak

linear with outlier negative trend or slope strong

nonlinear (curve) positive trend or slope weak

nonlinear (curve) negative trend or slope strong

nonlinear no trend or slope weak...