Year 2010 2011 2012 2013 2014 2009 GDP 16.2 16.7 17.3 14.4 15.0 15.5
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 table shows the Gross Domestic Product, or GDP (in trillions of dollars), for 2009 through 2014. (a) Use the regression capabilities of a graphing utility to find a mathematical model of the form y = at + b for the data. In the model, y represents the GDP (in trillions of dollars) and t represents the year, with t = 9 corresponding to 2009. (b) Use a graphing utility to plot the data and graph the model. Compare the data with the model. (c) Use the model to predict the GDP in the year 2024
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