The data show the bug chirps per minute at different temperatures. Find the regression​ equation, letting the first variable be the independent​ (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted​ value?   Chirps in 1 min 924 1150 840 1166 1087 930   Temperature ​(°​F) 77.5 84.6 74.1 91 79.6 79.7 What is the regression​ equation? What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per​ minute? What is wrong with this predicted​ value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an approximation. An unrounded value would be considered accurate. D. Nothing is wrong with this value. It can be treated as an accurate prediction.

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
6th Edition
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Bruce Crauder, Benny Evans, Alan Noell
Chapter5: A Survey Of Other Common Functions
Section5.3: Modeling Data With Power Functions
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The data show the bug chirps per minute at different temperatures. Find the regression​ equation, letting the first variable be the independent​ (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted​ value?
 
Chirps in 1 min
924
1150
840
1166
1087
930
 
Temperature
​(°​F)
77.5
84.6
74.1
91
79.6
79.7
What is the regression​ equation?
What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per​ minute?
What is wrong with this predicted​ value? Choose the correct answer below.
A. It is unrealistically high. The value 3000 is far outside of the range of observed values.
B. The first variable should have been the dependent variable.
C. It is only an approximation. An unrounded value would be considered accurate.
D. Nothing is wrong with this value. It can be treated as an accurate prediction.
 
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