STAT1008 Lecture Notes - Lecture 10: Point Estimation, Sample (Statistics), Projectile Motion
STAT1008 Week 4 Lecture A
● Scatterplot:
○ Graph of the relationship between 2 quantitative variables
○ Each response/individual is represented by a point
● Direction of Association direction:
○ Check the gradient of the linear association
○ Closer to -1 or +1 the stronger the linear association
○ R has no units and doesn’t depend on the units of measurements
○ Correlation between x and y is the same as y and x doesn’t matter about
order
● Correlation:
○ Dolphins and Raiders (outliers) influence the correlation aka the linear
association
○ Measure of the strength and direction of linear association between 2
quantitative variables
● Correlation caution:
○ R=0 means no linear association. The variable could still be otherwise
associated. Don’t treat it as an absence of any association e.g. Projectile
motion gives you a parabola hence R= approx 0 thus still associated
○ Correlation doesn’t imply causation!
○ Correlation is identical so it doesn’t really matter what is the x and what is
the y. Explanatory = x, response = y
● Covariance:
○ Has some limitations
○ Also measures linear relationship and does have units of measurement
○ Has a unit of measurement because it isn’t divided by standard deviation
like correlation
○ + = positive linear association - = negative linear association
○ Can’t measure it from -1<r<1 about strength of the association unlike
correlation
○ Correlation and covariance is relation as it is covariance/standard
deviation
● Statistical Inference:
○ Parameter = number that describes some aspect of a population
○ Statistics = a number that is computed from data in a sample
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Document Summary
Graph of the relationship between 2 quantitative variables. Each response/individual is represented by a point. Check the gradient of the linear association. Closer to -1 or +1 the stronger the linear association. R has no units and doesn"t depend on the units of measurements. Correlation between x and y is the same as y and x doesn"t matter about order. Dolphins and raiders (outliers) influence the correlation aka the linear association. Measure of the strength and direction of linear association between 2 quantitative variables. Don"t treat it as an absence of any association e. g. projectile motion gives you a parabola hence r= approx 0 thus still associated. Correlation is identical so it doesn"t really matter what is the x and what is the y. explanatory = x, response = y. Also measures linear relationship and does have units of measurement. Has a unit of measurement because it isn"t divided by standard deviation like correlation.
