or each of the following, draw a scatter plot for the variables, compute the correlation coefficient, state the hypothesis, test the significance of the correlation coefficient at α = 0.05, and give a brief explanation of the type of relationship. 1. The average gasoline price per gallon (in cities) and the cost of a barrel of oil are shown for a random selection of weeks in 2015. Is there a linear relationship between the variables? Oil ($) 51.91 60.65 59.56 52.86 45.12 44.21 Gasoline ($) 1.97 1.96 2.06 2.04 2.00 1.99
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.
For each of the following, draw a
give a brief explanation of the type of relationship.
1. The average gasoline price per gallon (in cities) and the cost of a barrel of oil are shown for
a random selection of weeks in 2015. Is there a linear relationship between the variables?
Oil ($) 51.91 60.65 59.56 52.86 45.12 44.21
Gasoline ($) 1.97 1.96 2.06 2.04 2.00 1.99
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