A biology student is investigating the claim that the temperature can be predicted by counting cricket chirps. She has collected the data in the table below and come up with the regression equation T=42.2+0.21r, where T is the temperature in degrees Fahrenheit and r is the number of chirps per minute. Would using this model to predict the temperature for 100 chirps per minute be an example of interpolation or extrapolation? Explain. r 66, 73, 81, 95, 116, 120, 138, 138 T 59, 55, 60, 67, 64, 68, 71, 73 Using the model to predict the temperature for a chirp rate of 100 chirps per minute is interpolation because 100 chirps per minute is outside the range of the values of r in the data set. Using the model to predict the temperature for a chirp rate of 100 chirps per minute is interpolation because 100 chirps per minute is inside the range of the values of r in the data set. Using the model to predict the temperature for a chirp rate of 100 chirps per minute is extrapolation because 100 chirps per minute is inside the range of the values of r in the data set. Using the model to predict the temperature for a chirp rate of 100 chirps per minute is extrapolation because 100 chirps per minute is outside the range of the values of r in the data set.
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.
A biology student is investigating the claim that the temperature can be predicted by counting cricket chirps. She has collected the data in the table below and come up with the regression equation T=42.2+0.21r, where T is the temperature in degrees Fahrenheit and r is the number of chirps per minute. Would using this model to predict the temperature for 100 chirps per minute be an example of interpolation or extrapolation? Explain.
| r | 66, | 73, | 81, | 95, | 116, | 120, | 138, | 138 |
|---|---|---|---|---|---|---|---|---|
| T | 59, | 55, | 60, | 67, | 64, | 68, | 71, | 73 |
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Using the model to predict the temperature for a chirp rate of 100 chirps per minute is interpolation because 100 chirps per minute is outside the
range of the values of r in the data set. -
Using the model to predict the temperature for a chirp rate of 100 chirps per minute is interpolation because 100 chirps per minute is inside the range of the values of r in the data set.
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Using the model to predict the temperature for a chirp rate of 100 chirps per minute is extrapolation because 100 chirps per minute is inside the range of the values of r in the data set.
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Using the model to predict the temperature for a chirp rate of 100 chirps per minute is extrapolation because 100 chirps per minute is outside the range of the values of r in the data set.
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