The data below is the amount of tar and nicotine in a sample of different brands of 100 mm, non-menthol, filtered cigarettes. a) Using the calculator, find a linear regression model that gives the amount of nicotine, N, as a function of the amount of tar, t. Write the function below. N(t)= b) use this model of nicotine to estimate the amount of nicotine in a cigarette if the amount of tar is listed as 21 mg. c) What is the correlation coefficient, r, for this model? r= Tar 5 16 17 13 13 14 9 15 2 15 13 14 15 16 7 17 Nicotine 0.4 1 1.2 0.8 0.8 1 0.8 1 0.2 1.1 0.
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.
The data below is the amount of tar and nicotine in a sample of different brands of 100 mm, non-menthol, filtered cigarettes.
a) Using the calculator, find a linear regression model that gives the amount of nicotine, N, as a
b) use this model of nicotine to estimate the amount of nicotine in a cigarette if the amount of tar is listed as 21 mg.
c) What is the
| Tar | 5 | 16 | 17 | 13 | 13 | 14 | 9 | 15 | 2 | 15 | 13 | 14 | 15 | 16 | 7 | 17 |
| Nicotine | 0.4 | 1 | 1.2 | 0.8 | 0.8 | 1 | 0.8 | 1 | 0.2 | 1.1 | 0.8 | 1 | 0.9 | 1.1 | 0.6 |
1.3 |
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