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

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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

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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

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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.

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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.

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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

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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

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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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