A regression model relating the logValue of a state's annual lobster catch to the number of licensed lobster Dependent variable is: LogValue fishers is shown to the right. Complete parts a and b. R-squared = 20.1% R-squared (adjusted) = 18.6% s = 0.4459 with 55 - 2 = 53 degrees of freedom Variable Coeff Intercept 5.71597 Fishers SE(Coeff) 0.3327 0.0000 P-value 17.2 50.0001 3.71 t-ratio 1.41805e - 4 0.0005 a) The number of licensed lobster fishers has fluctuated over the years between roughly 5000 and 10,000. Recently the number has been just over 7000. But licenses are in demand (and tightly restricted). What does the model predict the value of the catch would be in a year if there were 8500 licensed fishers? (Take care to interpret the coefficient correctly and to compute the inverse of the log transformation.) The model predicts that if there were 8500 licensed fishers, then the value of the catch in a year would be million. (Round to the nearest million as needed.)
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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