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Which of the following problems is illustrated by the below residuals' plot?Res dual Plot1000OutlierHeteroscedasticityImproperly formulated modelNone of the ab...

Question

Which of the following problems is illustrated by the below residuals' plot?Res dual Plot1000OutlierHeteroscedasticityImproperly formulated modelNone of the above

Which of the following problems is illustrated by the below residuals' plot? Res dual Plot 1000 Outlier Heteroscedasticity Improperly formulated model None of the above



Answers

Which of the following is a necessary assumption for performing inference analysis on the slope of a least squares regression line? (A) There is no strong skew or outliers in the data. (B) A straight line can be drawn through the set of paired observations in the scatterplot. (C) The distribution of the residuals is approximately uniform. (D) The distribution of the residuals is approximately linear. (E) The distribution of the residuals is approximately normal.

Which of the following can cost oils s meters to be biased and options are a terrorist conduct city Second option is a meeting and important variable on example Correlation coefficient off 0.95 between two independent variables, both included in the model. So oils estimators can be biased as omitting on important variable. So the answer would be the second option meeting an important variable. So that's the answer.

For this question, we're asked to find out which of the following can cost the usual oil egg statistics to be invalid. That is not to have see distributions on that H o. Um, So the first option is it's a rule scared dust TC. On the second option is a sample correlation coefficient off 0.95 between two independent variables there are in the model on the last option is omitting and important. Explain the tree variable. So which of them can cost the usual oil Are Stasi statistic to be invalid And the correct answer would be I and I on this is because the both of them generally cost is t statics. It's not have a redistribution on the H O because almost scared us to see is one of the classic linear Murdoch assumptions on an important omitted variable violet assumptions. F m l R. So the assumption contains no mention of the sample correlation except to rule out the case where the coalition is one so briefly would just say Yeah, yeah, Well, yeah, yeah, on the sample correlations. Yeah, So that will be there. So

The question gives us three different plots of residuals Onda Alceste to say whether about the appropriateness off Linnean bottles to fit the data. So these the residuals after refitted a model Onda, we now need to look at them and say, Oh, well, was that was it appropriate to fit a linear model on here? I've drawn out approximately what the graphs were showing. No, exactly. But hey also noted that zero shoes that we've got positive and negative residuals. So let's start by looking at Graham A. Okay, you can see the the residuals fairly, even their spread across spread around the graph. You got some higher, some fairly negative. But they do show what you were to describe is a fairly random pattern. There's no line we could draw in or, um, curve or the seems no passengers. That which showed the model for this one is definitely appropriate. It was appropriate to settle any model. What ever dated produce these residuals? No. Looking at babies, we've got quite a different shape hair we could draw in a cut. Andi, when you fitted residuals, you don't want them looking like they got a pattern because it shows that within this residuals you've now got trends which suggests a linear pattern wasn't what you should affect. I'm looking at this quite obvious curve to the second graph. It suggests it may be a quadratic or something along those lines might have been more appropriate. So when you got residuals that shows such a clear pattern, Alinea model was not appropriate. So looking at the third graf, this one is slightly more subjective because you can see in the first pair we've got very, very small residuals, which is actually really good at shoes, that the model was really good fest. But we then have this section which goes up into postive. This section of goes down. And when that was always a gap, it on this almost showed a trend in the latter half of sugar. Higher points. The residuals get more extreme weather that's positive or negative. So here one could say that it may not be appropriate to fit the model just because some would argue this bats a linear pattern on that selenium patent. So even in this paper, straight thestreet bits branches, so a pattern. So for this one, I would say a model may not be appropriate, but may not. And those are your three ounces. So the 1st 1? Yes, it was appropriates 2nd 1 No, it wasn't in. Those are both quite credit card. That said well.


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