In a regression analysis with multiple independent variables, multicollinearity can be caused by: a strong nonlinear relationship between the dependent variable and one or more independent variables a strong heteroskedastic relationship between the dependent variable and one or more independent variable a strong linear relationship between two or more independent variables none of the above

Answer! if you don’t mind, can you explain

Unaware that 35% of the 10000 voters in his constituency support him, a politician decides to estimate his political strength. a sample of 200 voters shows that 40% support him. a. what is the population? b. what is the parameter of interest? state its value c. what is the statistics of the interest? state its value d. compare your answers in (b) and (c) is it surprising they are different? if the politician were to sample another 200 voters, which of the two numbers would most likely change? explain

Typically a point in a three dimensional cartesian coordinate system is represented by which of the following answers in the picture !