In this problem, we use your critical values table to explore the significance of r based on different sample sizes. Critical Values for Correlation Coefficient r a = 0.05 a = 0.01 0.05 יח a = a = 0.01 a = 0.05 = 0.01 3 1.00 1.00 13 0.53 0.68 23 0.41 0.53 4 0.95 0.99 14 0.53 0.66 24 0.40 0.52 0.88 0.96 15 0.51 0.64 25 0.40 0.51 6. 0.81 0.92 16 0.50 0.61 26 0.39 0.50 0.75 0.87 17 0.48 0.61 27 0.38 0.49 8 0.71 0.83 18 0.47 0.59 28 0.37 0.48 9. 0.67 0.80 19 0.46 0.58 29 0.37 0.47 10 0.63 0.76 20 0.44 0.56 30 0.36 0.46 11 0.60 0.73 21 0.43 0.55 12 0.58 0.71 22 0.42 0.54 (a) Is a sample correlation coefficient p 0.84 significant at the a = 0.01 level based on a sample size of n = 4 data pairs? What about n = 10 data pairs? (Select all that apply.) %3D Yes, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 4 and a = 0.01. %3D No, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 4 and a = 0.01. %3D %3D Yes, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n = 4 and a = 0.01. No, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n = 4 and a = 0.01. Yes, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n = 10 and a = 0.01. No, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n = 10 and a = 0.01. No, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 10 and a = 0.01. %3D Yes, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 10 and a = 0.01. 0.05 level based on a sample size of n = 15 data pairs? What about n = 27 data pairs? (Select all that apply.) (b) Is a sample correlation coefficient p Yes, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 15 and a = 0.05. 0.43 significant at the a = No, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 15 and a = 0.05. No, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 27 and a = 0.05. Yes, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n = 27 and a = 0.05. No, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n = 15 and a = 0.05. %3D Yes, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n = 15 and a = 0.05. No, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n = 27 and a = 0.05. 4:55 PM Yes, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 27 and a = 0.05. ENG
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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