Which of the following are assumptions when fitting a least squares line in linear regression? (Select all that apply) Question 5 options: Linearity: The data should show a linear trend Nearly normal residuals: generally the residuals must be nearly normal Constant variability: Variability of points around the least squares line must remain roughly constant Symmetry: Lines of best fit should fit symmetrically along the median value

Answered: Which of the following are assumptions…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 5PPS

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Which of the following are assumptions when fitting a least squares line in linear regression? (Select all that apply)

Question 5 options:

	Linearity: The data should show a linear trend
	Nearly normal residuals: generally the residuals must be nearly normal
	Constant variability: Variability of points around the least squares line must remain roughly constant
	Symmetry: Lines of best fit should fit symmetrically along the median value

Definition Definition Middle value of a data set. The median divides a data set into two halves, and it also called the 50th percentile. The median is much less affected by outliers and skewed data than the mean. If the number of elements in a dataset is odd, then the middlemost element of the data arranged in ascending or descending order is the median. If the number of elements in the dataset is even, the average of the two central elements of the arranged data is the median of the set. For example, if a dataset has five items—12, 13, 21, 27, 31—the median is the third item in ascending order, or 21. If a dataset has six items—12, 13, 21, 27, 31, 33—the median is the average of the third (21) and fourth (27) items. It is calculated as follows: (21 + 27) / 2 = 24.

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