 # Aim: How do we use SPSS to create and interpret scatterplots? SPSS Assignment 1 Due Friday 2/12.

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Aim: How do we use SPSS to create and interpret scatterplots? SPSS Assignment 1 Due Friday 2/12

Scatterplots Scatterplot is a statistical figure that displays the relationship between two scale variables A scatterplot has two axes (one for each variable) The two scores for each participant are represented with a single dot – The pattern of the dots indicates the direction and strength of the relationship between the variables

When to use a scatterplot A scatterplot should be examined before calculating a correlation coeffient The nature of the relationship revealed by a scatterplot will help determine which correlation coefficient is appropriate

Creating a Scatterplot When one variable is intended to predict another, the predictor variable should be named Variable X and the variable being predicted should be named Variable Y – Dependent Variable = Y-axis – Independent Variable = X-axis While prediction is a major purpose of examining the relationship between two variables, sometimes researchers are interested in the relationship for other reasons, such as examining a relationship suggested by theory. When prediction is not involved, it is okay to put either variable on the x-axis and the other on the y- axis.

Interpreting the SPSS Output 1.Each dot on a scatterplot represents two scores for one participant. 2.Patterns of dots indicate positive/direct, negative/inverse relationship. 3.If there is a scatter, the dots do not form a perfectly straight line but are somewhat scatter. However the direction of the pattern can still be clear despite the scatter. The presence of a scatter indicates that the relationship is not perfect. 4.The relationship is strong, this is indicated by the fact that the dots are not scattered throughout the figure. Instead, they follow a clear pattern. 5.The relationship is linear. This means that the dots generally follow a straight line.

Perfect, Direct, Linear Relationship Dots form a single straight line with no scatter of dots around it, the relationship is perfect Also it is direct because the higher the y variable, the higher the x variable It is linear because the dots form a straight line

Strong, Inverse, Linear Relationships The relationship is inverse because participants with better x variables have fewer y variables – This creates an inverse pattern of dots, going from upper left to lower right of the scatterplot

Strong, Curvilinear Relationship For one part of the relationship it goes up and for the other part of the relationship, it changes directions and goes down (like a parabola) – The relationship is neither direct or inverse – It is curvilinear

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