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Select all that applyWhich of the following is true of qualitative forecast methods? Select all that apply!Multiple select question.Useful to forecast variables, such as product sales and product defectsUseful when historical numerical data is availableUsed when future results are suspected to depart markedly from results in prior periodsAttractive when historical data are not available
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- We can plot the residuals sequentially over time to look for correlated observations. How are violations indicated?-When positive residuals are shown consistently over time and negative residuals are shown consistently over time-When all the residuals are negative-When positive residuals and negative residuals alternate over a few periods, sometimes positive or negative for a couple of periods.-There is no detection method
- A crucial assumption in a linear regression model is that the error term is not correlated with the predictor variables. In general, when does this assumption break down?-When there are too many variables in the model-When important predictor variables are excluded.-The estimated standard errors of the OLS estimators are inappropriate-When the standard errors are distorted downward
- Select all that applyA useful method to interpret the estimated coefficient is to highlight the changing impact of x on p. For instance, given x = 10, we compute the predicted probability as 0.4256. For x = 11, the predicted probability is pˆ=0.4700. Therefore, as x increases by one unit from 10 to 11, the predicted probability changes. Which of the following is true? Select all that apply!The predicted probability increases by 0.0444 if x increases from 20 to 21The predicted probability changes by 0.0444 but it could increase or decreaseThe predicted probability increases by 0.0444The increase in pˆ will not be the same if x increases from 20 to 21