Idealization:Density curve = idealization = muNot thinking of real dataIntuition of xbar and is the menter of center we think?Variance of a a random variable:Correlation:Two random variables and how they relate.Idealization of rIndependence:One random variable does not relate to another random variableStronger form of uncorrelatednessIf correlation = 0 than the variables have no relation and are independent. Intuition is importnant here.Too find the stabilization of the second random variables:Variable minus the mean of the first random variables stablizaton aka mean and then square it. Multiply that by the probability of that second random variables and add then all up.Extending our intuition from describing histograms to a probability distribution. DO THIS. Understand how shape center mean apply to probability distributions.adding two random variables combines them. Could be correlated or not. Could be negatively correlated or not. How do you add negative correlations!?Linear transformation of a single random variables:Changing units of celcius to farienheit. C=5/9x -160/9?These are very common in the real world and are easy to set up with a set of rules.Rules: Linear transformation of a single random variableY=5/9X-160/9Y= a+bx5/9=BA=-160/9A = y interecept..?Example on collab, look at asap Idealization: - Density curve = idealization = muo Not thinking of real datao Intuition of xbar and is the menter of center we think?Variance of a a random variable:Correlation:- Two random variables and how they relate.- Idealization of r Independence:- One random variable does not relate to another random variable- Stronger form of uncorrelatedness - If correlation = 0 than the variables have no relation and are independent. Intuition is importnant here.Too find the stabilization of the second random variables:- Variable minus the mean of the first random variables stablizaton aka mean and then square it. Multiply that by the probability of that second random variables and add then all up. Extending our intuition from describing histograms to a probability distribution. DO THIS. Understand how shape center mean apply to probability distributions. adding two random variables combines them. Could be correlated or not. Could be negatively correlated or not. How do you add negative correlations!? Linear transformation of a single random variables:- Changing units of celcius to farienheit. C=5/9x -160/9?- These are very common in the real world and are easy to set up with a set of rules.Rules: Linear transformation of a single random variable- Y=5/9X-160/9- Y= a+bx- 5/9=B- A=-160/9- A = y interecept..?- Example on collab, look at