Thirty people were randomly selected and information about their working hours (X) and income (Y) for a month was collected. Suppose there is a linear relationship between X and Y. Assume that there is a linear relationship between X and Y. SST is equal to 79960 and SSR is equal to 57789. What is the standard error of the estimate. Round your answer to two decimal places.

A financial analyst wants to determine the relationship between a company's earnings per share (EPS, Y, in dollars) and its revenue (X, in million dollars). Assuming a linear relationship between Y and X, the analyst used the least-squares method and found that the Y-intercept = 1.75 and the slope = 0.42. Also, the sum of squares total (SST) and the error sum of squares (SSE) were equal to 82000.12 and 15200.43, respectively.Based on this information, what is the coefficient of determination? Round your final answer to four decimal places. Note: don't put your answer in percentage form.

A consumer's spending is widely believed to be a function of their income. To estimate this relationship, a university professor randomly selected 19 of his students and collected information on their spending (Y, in dollars) and income (X, in dollars) patterns in week 6 of the semester. Assuming a linear relationship between Y and X, the professor used the least-squares method and found that the Y intercept = 20.90 and the slope = 0.66. Also, the sum of squares total (SST) and the error sum of squares (SSE) were equal to 65600.74 and 12769.51, respectively. Based on this information, the coefficient of determination can be interpreted as follows a. 80.53% of the variation in weekly income is explained by the variation in a student's weekly spending. b. 19.47% of the variation in weekly spending is explained by the variation in a student's weekly income. c. 80.53% of the variation in weekly spending is explained by the variation in a student's weekly income. d. 19.47% of the variation in weekly income is explained by the variation in a student's weekly spending.

A consumer's spending is widely believed to be a function of their income. To estimate this relationship, a university professor randomly selected 19 of his students and collected information on their spending (Y, in dollars) and income (X, in dollars) patterns in week 6 of the semester. Assuming a linear relationship between Y and X, the professor used the least-squares method and found that the Y intercept = 20.90 and the slope = 0.66. The professor also found that the standard error of the slope was 0.08. Based on this information, what conclusion should you reached at the 5% level of significance when testing the null hypothesis that there is no linear relationship between the two variables, X and Y? a. There is sufficient evidence at the 5% level of significance to conclude that there is no significant linear relationship between X and Y. b. There is sufficient evidence at the 5% level of significance to conclude that there is a significant linear relationship between X and Y. c. There is sufficient evidence at the 5% level of significance to conclude that there is a significant linear relationship between the Y intercept and the slope. d. There is insufficient evidence at the 5% level of significance to conclude that there is a significant linear relationship between X and Y.

A UQ master student collected data on annual wages (Y, in $'000) and years of study (X) from a random sample of 10 part-time workers to test this proposition. Assuming a linear relationship between Y and X, the student used a least-squares method and found that the Y intercept = -21.50 and the slope = 9.73. The student also found that the standard error of the slope was 1.61. Based on this information, what is the value of the t test statistic if you are testing the null hypothesis that there is no linear relationship between the two variables, X and Y? Round your final answer to three decimal places.

A consumer's spending is widely believed to be a function of their income. To estimate this relationship, a university professor randomly selected 19 of his students and collected information on their spending (Y, in dollars) and income (X, in dollars) patterns in week 6 of the semester. Assuming a linear relationship between Y and X, the professor used the least-squares method and found that the Y intercept = 20.90 and the slope = 0.66. The professor also found that the standard error of the slope was 0.08. Based on this information, what is the value of the t test statistic if you are testing the null hypothesis that there is no linear relationship between the two variables, X and Y? Round your final answer to two decimal places.