The data set below represents a random sample of nine children. The children's age in months and weights in pounds are recorded. Age (months), x Weight (pounds), y 18 20 24 26 27 30 34 39 23 25 24 32 30 29 36 40 45 Ex = 260 Ey = 284 Exy = 8676 Ex2 = 8046 Ey? = 9416 A. Calculate the sample correlation coefficient r. Round to 4 decimal places. B. Make a conclusion about the type of correlation O A. Strong positive linear correlation O B. No linear correlation O C. Strong Negative linear correlation O D. Weak Negative linear correlation C. Find the equation of the regression line for the given data. Round your answers to the thousandths place.
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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