(a) Is a sample correlation coefficient p = 0.86 significant at the a = 0.01 level based on a sample size of n = 4 data pairs? What about n = 12 data pairs? (Select all that apply.) O 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. O Yes, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size ofn = 4 and a = 0.01. O Yes, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 12 and a = 0.01. O No, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 12 and a = 0.01. O 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. O No, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n = 12 and a = 0.01. O Yes, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size ofn = 12 and a = 0.01. O 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. (b) Is a sample correlation coefficient p = 0.43 significant at the a = 0.05 level based on a sample size of n = 18 data pairs? What about n = 29 data pairs? (Select all that apply.) O No, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n = 18 and a = 0.05. O Yes, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size ofn = 18 and a = 0.05. O Yes, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 18 and a = 0.05. O No, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 18 and a = 0.05. O Yes, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n = 29 and a = 0.05. O Yes, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 29 and a = 0.05. O No, because the absolute value of the given correlation coefficient is greater than or equal to that for a sample size of n 29 and a = 0.05. O No, because the absolute value of the given correlation coefficient is smaller than that for a sample size of n = 29 and a = 0.05. (c) Is it true that in order to be significant, ap value must be larger than 0.90? larger than 0.70? larger than 0.50? What does sample size have to do with the significance of p? Explain your answer. o Yes, a larger correlation coefficient of 0.70 means that the data will be significant. o No, a larger sample size means that a smaller absolute value of the correlation coefficient might be significant. o No, sample size has no bearing on whether or not the correlation coefficient might be significant. o Yes, a larger correlation coefficient of 0.90 means that the data will be significant. o Yes, a larger correlation coefficient of 0.50 means that the data will be significant.
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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