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Problem 5: Fisheries The data set provided in StatCrunch contains a simple random sample of 29 wild fisheries. A marine biologist is researching the relationship

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Problem 5: Fisheries The data set provided in StatCrunch contains a simple random sample of 29 wild fisheries. A marine biologist is researching the relationship between biomass (total mass of living matter within a given area) and other environmental factors measured for each wild fishery. Biomass is measured in metric tons. Consider the explanatory variables [heavy metal concentration (Metal), measured in mg/g, number of fish species in the fishery (Species), and the area of the fishery (Area), measured in acres] and use them to attempt to predict a fishery's total biomass (Biomass). The dataset is called "Fisheries." A marine biologist believes the explanatory variable, "Area" will be the best predictor of the response variable. Investigate the relationship between the explanatory variables and response variable "Biomass" to validate her claim by doing the following: a) Make three separate scatterplots where each scatterplot will present one of the explanatory variables graphed with the response variable "Biomass." Copy and paste them in your solutions (use Graph > Scatter Plot in StatCrunch). Title and label the graphs properly. b) Interpret the scatterplot of "Area" and "Biomass" using trend, strength, and shape (form) in one complete sentence. c) Calculate the three correlation coefficients using Stat > Summary Stats > Correlation in StatCrunch. Each correlation will be calculated using one of the explanatory variables vs. the response variable "Biomass". Provide these three values in your document. d) Comment on the marine biologist's variable belief about the explanatory variable. Does the"Area" explanatory variable have the strongest relationship with the response variable? Answer this question and provide your reason why in a complete sentence

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