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 30003000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 833 1187 1170 759 1068 1018 Temperature (degrees°F) 72.4 92.6 83.6 64.1 88.1 83.3 What is the regression equation? ModifyingAbove y with caretyequals=24.36plus+0.056x (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.) What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best predicted temperature when a bug is chirping at 3000 chirps per minute is ?????degrees°F. (Round to one decimal place as needed.)
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
|
Chirps in 1 min
|
833
|
1187
|
1170
|
759
|
1068
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1018
|
|
|---|---|---|---|---|---|---|---|
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Temperature
(degrees°F)
|
72.4
|
92.6
|
83.6
|
64.1
|
88.1
|
83.3
|
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