original using regression equation, 195.47 20.26x. Therefore we could justify th

Question

original using regression equation, 195.47 20.26x. Therefore we could justify the original regression equation to analyze the relationship between age and of Orions between 2 and years of age, even though the data set contains an influential An outlier may or may not be an influential observation, and an influential o potential may or may not be an outlier. Many statistical software packages identify outliers and influential observations. A Warning on the Use of Linear Regression The idea behind finding a line is based on the assumption that the data points are scattered about regression however, the data points are scattered about a curve a Frequently, instead of a line, as depicted in Fig. 14.13(a) FIGURE 14.13 (a) Data points scattered about a curve (b) inappropriate line fit to the data points (a) (b) One can still compute the values of bo and bi to obtain a regression line for these data points. The result, however, will yield an inappropriate fit by a line, as shown in 14.13(b), when in fact a curve should be used. For instance, the regression line Fig. suggests that y-values in Fig. 3(a) will keep increasing when they have actually 14.13 begun to decrease. KEY FACT 14.3 Criterion for Finding a Regression Line ne for a set of data points finding a regression

Explanation / Answer

One of the important assumptions for using linear regression is:

Straight enough condition: the shape of the scatterplot must be linear or one cannot use linear regression at all.

Therefore, it seems that option a is the point of the given Figure.

Option a (ans)

Related Questions

Navigate

• Browse (All)
• Browse O
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.