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● Using the slope and mean values, the y-intercept of the regression line is calculated.
● Predicted y-values are calculated based on the linear equation formed by the slope and y-intercept.
● The data points and the regression line are plotted on the same graph to visualise the relationship between x and y.
● Labels for x and y axis are added to the plot as well as, a title is provided to describe the purpose of the plot. The
plot is displayed for visualisation.
● The estimated slope and intercept values are printed to provide insights into the relationship between the variables.
Correlation
The word correlation is used in daily life to denote some forms of association. We might say that we have noticed
a correlation between smog and asthma attacks. However, in statistical terms, we use correlation to express an
association between two quantitative variables. It measures the strength or degree of relationship between two
variables. The relationship may be causal. We also presume that the association is linear, i.e., one variable increases or
decreases a set amount for a unit increase or decrease in the other.
Perfect High Low Low High Perfect
Positive Positive Positive No Negative Negative Negative
Correlation Correlation Correlation Correlation Correlation Correlation Correlation
Types of Correlation
There are four types of correlations:
r = -1
r = +1
Positive Negative
Correlation Correlation
r = 0 No Correlation Non-linear correlation
334 Touchpad Artificial Intelligence (Ver. 3.0)-XI

