8.0 10.0 12.0 14.0 16.0 Years Since 1990 Residuals
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.
Oakland passengers The
number of passengers departing from Oakland (CA)
airport month by month since the start of 1997. Time
is shown as years since 1990, with fractional years
used to represent each month. (Thus, June of 1997
is 7.5—halfway through the 7th year after 1990.)
www.oaklandairport.com
b) What does the value of R2
d) Would you use this model to predict the numbers of
passengers in 2010 (YearsSince1990 = 20) Explain.
e) There’s a point near the middle of this time span with
a large negative residual. Can you explain this outlier?
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