if the conditional variation of the random errors is not constant (i.e., var(ei|xi)≠symbol of standard deviation^2), then we say random errors are_____.
a. homoscedastic
b.exogenous
c.heteroskedastic
d.serially correlated
here homoscedastic refers to the conditon where variance is constant while heteroskedastic is when not constant
option C is correct,
if the conditional variation of the random errors is not constant (i.e., var(ei|xi)≠symbol of standard deviation^2),...
Conditional expectation.
Question 2 (10.0 marks) Previous 1 2 Validate Mark Unfocus Help ndependently or the Suppose the number o calls attempte per hour to a telephone exchange has Posso tribution with mean Suppose there is only 80% chance that an attempted call is connected a other calls connected. Let X be the number of calls that are connected in an hour. We ask you to find the mean and variance of X. In reality, this is mainly a theory...
Confidence Interval about a Population Standard Deviation 3) Consider the same information as in Example 2 on page 336, section 7.3, but use a confidence level of 90% instead of 95% Write your solution just like in the example. Show all work and use the formulas (do not use any technology here!) Note that the solution shown in the example is quite detailed. Your solution could be shorter, start where it says Using Table A-4 on page 337, and continue...
1. A random sample of n measurements was selected from a population with standard deviation σ=13.6 and unknown mean μ. Calculate a 90 % confidence interval for μ for each of the following situations: (a) n=45, x¯¯¯=89.8 ≤μ≤ (b) n=70, x¯¯¯=89.8 ≤μ≤ (c) n=100, x¯¯¯=89.8 ≤μ≤ (d) In general, we can say that for the same confidence level, increasing the sample size the margin of error (width) of the confidence interval. (Enter: ''DECREASES'', ''DOES NOT CHANGE'' or ''INCREASES'', without the...
6. Step 6: the formula for the intercept (i.e. constant: denoted as Alpha Hat) of a bivariate regression is Find the Alpha hat= !! As the formula indicates, simply you need put the y and subtract the product of and the answer you responded in question 5 above. 3 7. Now you do have regression equation. By plugging in x in the above equation you can fill in the third column below. Once you fill in the third column, by...
Problem 2. Consider the following joint probabilities for the two variables X and Y. 1 2 3 .14 .25 .01 2 33 .10 .07 3 .03 .05 .02 Find the marginal probability distribution of Y and graph it. Show your calculations. b. Find the conditional probability distribution of Y (given that X = 2) and graph it. Show your calculations. c. Do your results in (a) and (b) satisfy the probability distribution requirements? Explain clearly. d. Find the correlation coefficient...