how would you describe the relationship between two variables on a scatter plot?
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Scatter plots show how much one variable is affected by another. The relationship between two variables is called their correlation . ... If the data points make a straight line going from the origin out to high x- and y-values, then the variables are said to have a positive correlation .
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Two variables x and y have a deterministic linear relationship if points plotted from (x,y) pairs lie exactly along a single straight line. In practice it is common for two variables to exhibit a relationship that is close to linear but which contains an element, possibly large, of randomness.
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A scatter plot is a graph of points that show the relationship between two different pieces of data, while a line graph is a graph that shows information via a connected line.
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['Begin by plotting all your data. ... ', 'Draw a shape that encloses all of the data, (try to make it smooth and relatively even). ... ', 'Draw a line that divides the area that encloses the data in two even sized areas. ... ', 'Congratulations!']
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Typically, the independent variable is on the x-axis, and the dependent variable on the y-axis. The chart displays values at the intersection of an x and y axis, combined into single data points. The main purpose of a scatter plot is to show how strong the relationship, or correlation, between the two variables is.
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The slope and y-intercept values indicate characteristics of the relationship between the two variables x and y. The slope indicates the rate of change in y per unit change in x. The y-intercept indicates the y-value when the x-value is 0.
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['A title which describes the experiment. ... ', 'The graph should fill the space allotted for the graph. ... ', 'Each axis should be labeled with the quantity being measured and the units of measurement. ... ', 'Each data point should be plotted in the proper position. ... ', 'A line of best fit.']
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Such a pattern is called a linear relationship because it represents a straight line relationship between the coordinates of the points. We can describe the relationship between x and y in words as follows: The y-coordinate is three times the x-coordinate. This means y is three times x.
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['Identify the input values.', 'Identify the output values.', 'If each input value leads to only one output value, classify the relationship as a function.']
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Key Takeaways. A linear relationship (or linear association) is a statistical term used to describe a straight-line relationship between a variable and a constant. Linear relationships can be expressed either in a graphical format or as a mathematical equation of the form y = mx + b.
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['Data correlation. When the data points form a straight line on the graph, the linear relationship between the variables is stronger and the correlation is higher (Figure 2).', 'Positive or direct relationships. ... ', 'Negative or inverse relationships. ... ', 'Scattered data points. ... ', 'Non-linear patterns. ... ', 'Spread of data. ... ', 'Outliers.']
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Correlation describes the relationship between two sets of data.
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The Axes. The independent variable belongs on the x-axis (horizontal line) of the graph and the dependent variable belongs on the y-axis (vertical line).
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A positive correlation is a relationship between two variables in which both variables move in the same direction. Therefore, when one variable increases as the other variable increases, or one variable decreases while the other decreases.
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A linear relationship (or linear association) is a statistical term used to describe a straight-line relationship between two variables. Linear relationships can be expressed either in a graphical format or as a mathematical equation of the form y = mx + b. Linear relationships are fairly common in daily life.
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Correlation means there is a relationship or pattern between the values of two variables. A scatterplot displays data about two variables as a set of points in the x y xy xy -plane and is a useful tool for determining if there is a correlation between the variables.
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It expresses the relationship of two variables (say x and y) when they are multiplicatively connected to a constant so that either their ratio or their product yields a constant. So we either have c = x / y or c = x · y where c is then the constant of proportionality between x and y.