The Pearson correlation is always positive

The higher the R² of  a linear model, the higher is the Pearson correlation between predicted values and observed values

The higher the correlation between two variables is, the higher will be the absolute value of the slope of the least square line

The linear model is the best fitted model if the Pearson correlation is high

The error for the point corresponding to the mean of y is 0 

Their sum is 0

They are equal to the difference  (xi-yi)

They are equal to the difference between the y value of a point and that of the point corresponding to its projection on the line

Passes through the median point

Minimizes the sum of errors

The estimators of the intercept and slope are unbiased

Maximizes the likelihood function

A point that is an outlier for variable  Y

A point that dramatically changes the slope of the line when removed

A point that is an outlier for variable X 

A point that have a Cook's distance more than 1

y=a/(1-exp(-bx))

y=x/(a+bx)

y=a+bx²

y=a+bsin(x)

of accepting H0 when it is false

of rejecting H0 when it false

The probability of accepting H0 when it is true

of rejecting H0 when it is true

assumes that the distribution of the variable is Normal

is a test for comparing two medians

is a test for comparing two variances

is a test for comparing two means

is the probability of H0 true given data

Is a conditional probability

is the probbaility of data given that H0 is false

if it is equal to 0.09 we accapt H0

Can be tested for significance

does not assume that the two variables have a Normal distribution

 Is a measure of linear statistical relationship

  Is a measure of non-linear statistical relationship

is characterized by its bias

is characterized by a distribution function

is characterized by its power

is a random variable