Suggest us how to improve StudyLib For complaints, use another form. The residual is about 17 thousand people; the LSRL predicts Solve Linear Equations and analyze linear functions 1. See graph at right. The hot water will approach room temperature but will never cool more than that. The predictions from the model may be too low. Math 2 Name Lesson

Predicted weight is 1. See scatterplot at right. Yes, the residual plot appears randomly scattered with no apparent pattern. The selling price is much closer to what was predicted in Smallville, so she should predict that the home is in Smallville. The graph is a parabola opening upward. From left to right the graph is always increasing.

The measurements had one decimal place.

Yes, the residual plot shows random homewkrk with no apparent pattern. The predictions from the model may be too low. The domain is all real numbers and the range is y!

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The x-intercepts are at 1, 0 and 3, 0. The domain and range are both all numbers. About 5 — 1. The vertex is at 2, —1. The residuals are positive, so we expect the actual values to be greater than the predicted values. You can add this connecttions to your saved list Sign in Available only to authorized users.

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See plot below right. The negative slope means there is a negative association. With a car readily available these teens might simply be driving more and the extra time on the road is causing them to be in more crashes. The predicted attendance is between 11, and 25, people.

Add this document to collection s. The cold actually lasted 0. The LSRL model would show the expected cost of a 16 oz burger to be 0. From left to right the graph is always increasing.

The form is linear, the direction is negative, the strength is moderate, and there are no apparent outliers. See scatterplot at right.

The y-intercept would be the cost of the hamburger with no meat. Math 2 Name Lesson With each additional degree of temperature, we predict an increase of park visitors. There is no real solution because you cannot take the square root of a negative number.

We predict that when the pencil is so short there is no paint left, the pencil is expected to weigh 1. Strong positive linear association with one apparent coonnections at 2. The residual is about 17 thousand people; the LSRL predicts A positive residual means the pencil weighed more than was predicted by the LSRL model.

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Connrctions y-intercept is the number of days a cold will last for answerd person who takes no supplements. The y-intercept of 5 means that we expect a person who has not taken any supplement to have a cold that lasts five days; more generally, the average cold is five days long. The x-intercept is at 6, 0 and the y-intercept is at 0, — There is no line of symmetry. She should add 1 first, since the addition is placed inside the absolute value symbol, which acts as a grouping symbol.

Predicted weight is 1. The hot water will approach room temperature but will never cool more than that.