Question: How does a bivariate regression model differ from a multiple regression model? Multiple Choice A bivariate regression has only one dependent and independent variable but
How does a bivariate regression model differ from a multiple regression model?
Multiple Choice
A bivariate regression has only one dependent and independent variable but a multiple regression has more than one dependent variable and may have many independent variables.
A bivariate regression has more than one dependent variable and only one independent variable where a multiple regression has one dependent variable and may have many independent variables.
A bivariate regression has only one dependent and many independent variables but a multiple regression has one dependent variable, but may have many independent variables.
A bivariate regression has only one dependent and independent variable but a multiple regression has one dependent variable and may have many independent variables.



Let {Xiji=1 36 be the sequence of continuous IIDRV with EXi = 40, Var Xi = 144, i = 1, ..., 36 and A36 Eil Xi = 36 (a) By using the Markov's inequality estimate P( A36 0, and any numbert > 0: P(X >D)SH. Note that the Markov inequality is restricted to non-negative random variables. Chebyshev inequality For a random variable X with (finite) mean / and variance of, and for any number t 2: 0, P(X -#| 20)ST. Remark: When Markov inequality is applied to (X" - /)", we obtain Chebyshev's inequality. Markov inequality is also used in the proof of Hoeffding's inequality. Hoeffding versus Chebyshev 4 points possible (graded) Let X], X2, ...;X, " Unif (0, b) be n i.i.d. uniform random variables on the interval [0, b] for some positive b. Suppose n is small (i.e. in
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