1) The number of adults in a certain county with a college degree has been rising since the year 2005. Let x represent the number of years since the year 2000, and let y represent the number of 1000s of adults in the county with a college degree for year Х. Number of Years Number of Adults with a College Since 2005 (x) Degree (y in 1000s) 10 4 18 52 (a) Use the data to create a model of the form y = ax2 + bx + c. (b) Use the model to approximate the number of adults in the county who will have a college degree for the year 2015.
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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