125 100 75 50 + 10 20 30 40 Years Since 1970 Error
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.
istration about their success in predicting hurricane
miles) for predicting hurricane locations 24 hours in the
ricane) occurred.In Chapter 6, we could describe this relationship only
in general terms. Now we can learn more. Here is the
regression analysis:
Dependent variable is 24Error
R-squared = 68.7%
s = 16.44 with 41 - 2 = 39 degrees of freedom
Variable Coefficient SE(Coeff) t-Ratio P-Value
Intercept 132.3 5.043 26.2 ...0.0001
Years Since 1970 -2.01 0.217 -9.25 ...0.0001
a) Explain in words and numbers what the regression says.
b) State the hypothesis about the slope (both numerically
and in words) that describes how hurricane prediction
quality has changed.
c) Assuming that the assumptions for inference are satisfied,
perform the hypothesis test and state your conclusion.
Be sure to state it in terms of prediction errors and years.
d) Explain what the R-squared means in terms of this
regression.
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