#mathsflashcards_unit3_chapter3

Correlation does not equal ____ ::Causation

What does ‘r’ represent in Bivariate Data Analysis::‘r’ usually represents the Correlation Coefficient

What does ’’ represent in Bivariate Data Analysis::’ usually represents the coefficient of determination.

What is the coefficient of determination::The Coefficient of determination shows how good the Linear Model is for describing a particular trend. basically, is a percentage, the closer to 1 it is the more the variation in the response variable can be explained by variation in the explanatory variable.

If we write that: ::47% of the variation in {Response Variable} can be explained by variation in {Explanatory Variable}

How can we determine the Correlation Coefficient from the Coefficient Of Determination or vis versa?::since the Correlation Coefficient is and the Coefficient Of Determination is we can just square root to get or square the value to get

What is the confounding variable?::The Confounding variable is an unknown factor that influences another relationships, for example An increase in Ice cream sales correlates with an increase in murders, the confounding variable in this could be that both murders and Ice-cream sales are influenced by the heat.

A survey of a large number of cities revealed a high correlation between the number of police offices and the nuber of crimes commited. Jerry says that more police officers causes higher crime rates is jerry correct? ? It does not make any snese to conclude that the number of olice officers would be causing more crimes to be commited,Cities with high crime rates would actually need higher numbers of police officers. It is more than likely that both of these variables increase in increase in cities with higher populaitons, Lower Economic Status, and other possible Lurking (Confounding) variables. Statistically we also cannot confirm that it is causing it as Correlation does not equal Causation ever.

If R is positive, what does this say about the Linear Relationship?::The Linear relationship is going from left to right. As the explanatory variable increases so does the response variable.

When would you use a row percentaged two way frequency table? ? When the explanatory variable uses the rows to show its different categories. Instead of the explanatory variables being entered into the columns of a two way frequency table

if what is the strength and direction of the correlation::Perfect Positive Correlation

if what is the strength and direction of the linear correlation::No Linear Correlation

if what is the strength, and direction of the linear correlation::Moderate Positive Correlation

Does the area of the lawn cause Abdul to spend more time on mowing?::Correlation ≠ Causation, not necessarily, cannot confirm nor deny

Given this:is this a good way to write the equation?::No, should use variables that relate the context, e.g. M and F instead of X and Y

Given this Distribution if you want to find the least squares regression line of y on x, should x be list 1 or should y be list 1::Y should be list one. List one is what it equals e.g. if y is list one the equation takes the form of