If a sample size is high, n=5000, the correlation coefficient
will most likely be...
a. Positive
b. Negative
c. Significant
d. Non-significant
If a sample size is high, n=5000, the correlation coefficient will most likely be... a. Positive...
Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents a significant linear correlation. Use a significance level of 0.05. r =-0.816, n =5 A. Critical values: = +/- 0.878, no significant linear correlation B. Critical values: =0.950, significant linear correlation C. Critical values: = +/- 0.878, significant linear correlation D. Critical values: = +/-0.950, no significant linear correlation
Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents a significant linear correlation. Use a significance level of 0.05. r = 0.543, n = 25. SHOW WORK Group of answer choices A)Critical values: r = ± 0.396, significant linear correlation B)Critical values: r = ± 0.487, significant linear correlation C)Critical values: r = ± 0.396, no significant linear correlation...
Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents a significant linear correlation. Use a significance level of 0.05. r=0.543, n = 25 Critical values: r = ±0.487, significant linear correlation Critical values: r = ±0.487, no significant linear correlation Critical values: r = ±0.396, no significant linear correlation Critical values:r = ±0.396, significant linear correlation.
Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents a significant linear correlation. Use a significance level of 0.05. r = 0.543, n = 25. A. Critical values: r = plus or minus 0.487, no significant linear correlation B. Critical values: r = plus or minus 0.396, no significant linear correlation C. Critical values: r = plus or minus...
Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents a significant linear correlation. Use a significance level of 0.05. r = 0.353, n = 15
Test for a positive correlation using the sample correlation r=0.33 and the sample size n=30. State the null and alternative hypotheses. Find the test statistic. Round your answer to two decimal places. t= Find the p-value. Round your answer to three decimal places. The p-value is . What is the conclusion, using a 5% significance level? ...
(a) Suppose n = 6 and the sample correlation coefficient is r=0.894. IS significant at the 1% level of significance (based on a two-tailed test)? (Round your answers to three decimal places.) critical Conclusion: Yes, the correlation coefficient p is significantly different from 0 at the 0.01 level of significance. No, the correlation coefficient p is not significantly different from 0 at the 0.01 level of significance. (b) Suppose n = 10 and the sample correlation coefficient is r =...
4.7 Let r'n be the Pearson correlation coefficient from a sample size of n. It is known that rn is asymptotically distributed as N (p, (1 – p2)2/n), where p is the population correlation coefficient. Show that Fisher's Z-transformation Z = { In((1 + ra)/(1 – in)) is actually a variance-stabilizing transformation.
QUESTION 21 The range of correlation coefficients is most likely from: a. 0 to +1.0. b. 0 to +2.0. c. -1 to 0. d. -1 to +1. QUESTION 22 The determination of the success of an active portfolio is: a. Positive alpha/low R2. b. Positive alpha/high R2. c. Negative gamma/high R2. d. High beta/low R2.
If the Durbin-Watson statistic is greater than 3, then Group of answer choices positive serial correlation is likely an issue. non-stationarity is likely an issue. negative serial correlation is likely an issue. spurious regression is likely an issue. Suppose you estimate a multiple regression model using OLS and the coefficient of determination is very high (above 0.8), while none of the estimated coefficients are (individually) statistically different from zero at the 5-percent level of significance. The most likely reason for...