The following data represent the number of calories per serving and the number of grams of sugar per serving for a random sample of high-fiber cereals. Complete parts (a) through (d) below. 240 Calories, x 250 150 190 210 D Sugar, y 17 13 14 17 12 Click the icon to view the table of critical values of the correlation coefficient. (a) A scatter diagram of the data is shown. What type of relation appears to exist between calories and sugar content? O A. There appears to be a strong linear relationship between calories and sugar content. O B. There appears to be a strong nonlinear relationship between calories and sugar content. There appears to be little or no relationship between calories and sugar content. (b) Determine the correlation coefficient between calories and sugar content. The correlation coefficient is .097 . (Type an integer or decimal rounded to three decimal places as needed.) Determine the critical value for the correlation coefficient.
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.
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