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REGRESSION ANALYSIS: DETECTION, EFFECTS AND REMEDIAL MEASURES OF DEPARTURES ON ASSUMPTIONS OF REGRESSION MODEL Departures/Violations on Graphical Statistical Effects of the violations on the model Remedial Measures Assumptions 1. The error terms do not have constant variance. 2. The error terms are not normally distributed. 3. The number of observations n is less than or equal to the number of parameters to be estimated.

REGRESSION ANALYSIS: DETECTION, EFFECTS AND REMEDIAL MEASURES OF DEPARTURES ON ASSUMPTIONS OF REGRESSION MODEL Departures/Violations on Graphical Statistical Effects of the violations on the model Remedial Measures Assumptions 1. The error terms do not have constant variance. 2. The error terms are not normally distributed. 3. The number of observations n is less than or equal to the number of parameters to be estimated.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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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REGRESSION ANALYSIS: DETECTION, EFFECTS AND REMEDIAL MEASURES OF DEPARTURES ON ASSUMPTIONS OF REGRESSION MODEL Departures/Violations on Graphical Statistical Effects of the violations on the model Remedial Measures Assumptions 1. The error terms do not have constant variance. 2. The error terms are not normally distributed. 3. The number of observations n is less than or equal to the number of parameters to be estimated.
Transcribed Image Text:REGRESSION ANALYSIS: DETECTION, EFFECTS AND REMEDIAL MEASURES OF DEPARTURES ON ASSUMPTIONS OF REGRESSION MODEL Departures/Violations on Graphical Statistical Effects of the violations on the model Remedial Measures Assumptions 1. The error terms do not have constant variance. 2. The error terms are not normally distributed. 3. The number of observations n is less than or equal to the number of parameters to be estimated.
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