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Summary Scatter Plots and Regression Lines - Mathematics Grade 12 (IEB)

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Covers the various sections relating to Scatter Plots and Regression Lines within the Mathematics syllabus. (Paper 2 section) Includes notes from the textbook, as well as additional class, video and research information, diagrams and practice questions. Applicable to all IEB Grade 12s. Written by a 95% student.

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February 23, 2021
Number of pages
4
Written in
2020/2021
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Summary

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Scatter plots and regression lines
Univariate data
= single values

Bivariate data
= two variables at the same time for comparison

Graphically the relationship between two variables can be shown by means of a scatterplot.
One variable is placed on the x-axis and on the y-axis.




A linear relationship may exist between two variables.
The straight line that best represents this relationship is called the line of best fit or the least
squares regression line.

y = a + bx (y = c + mx in statistical format)

y - shows that the equation represents a trend that doesn’t give actual y values, but predicted y
, values.
a - y-intercept of the line
b - the gradient

(Average x; average y) is a point that lies on the line of best fit.

Correlation coefficient
=r
Indicates how well the least squares regression line represents the data.
Tells us the type of relationship (positive or negative) as well as the strength of the relationship.
A numerical value, between -1 and 1.
(r is not the slope and therefore is not affected by the flipping of the x and y)

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