Fifty-four wild bears were anesthetized, and then Correlation Results their weights and chest sizes were measured and Correlation coeff, r: 0.960345 listed in a data set. Results are shown in the Critical r: +0.2680855 accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an P-value (two tailed): 0.000 anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of a = 0.05. There is one critical value at r= Is there sufficient evidence to support the claim that there is a linear correlation betweer the weights of bears and their chest sizes? Choose the correct answer below and, if necessary, fill in the answer box within your choice. (Round to three decimal places as needed.) O A. No, because the test statistic falls between the critical values. B. No, because the absolute value of the test statistic exceeds the critical value. O C. Yes, because the absolute value of the test statistic exceeds the critical value. O D. Yes, because the test statistic falls between the critical values. O E. The answer cannot be determined from the given information.
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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