For a sample of 30 Australian cities, a sociologist studies the crime rate in each city (crime per 100,000 residents) as a function of its poverty rate (in %) and its average income (in $1,000). A portion of the regression results shows that the coefficients for poverty and average income are 54.22 and 5.10, respectively. Based on this information, what is the value of test statistic used to test the null hypothesis that X1 has no significant effect on Y at the 5% level of significance, if the standard error of the slope of Y with variable X1 equals 15.50. Round your final answer to two decimal places. Note: Y = crime rate in each city (crime per 100,000 residents); X1 = poverty rate (in %); and X2 = average income (in $1,000).

For a sample of 40 Australian cities, a sociologist studies the crime rate in each city (crime per 100,000 residents) as a function of its poverty rate (in %) and its average income (in $1,000). A portion of the regression results shows that the coefficients for poverty and average income are 54.22 and 5.10, respectively. Based on this information, what is the upper critical value used to test the null hypothesis that X1 has no significant effect on Y at the 1% level of significance? Note: Y = crime rate in each city (crime per 100,000 residents); X1 = poverty rate (in %); and X2 = average income (in $1,000).

For a sample of 30 Australian cities, a sociologist studies the crime rate in each city (crime per 100,000 residents) as a function of its poverty rate (in %) and its average income (in $1,000). A portion of the regression results shows that the coefficients for poverty and average income are 54.22 and 5.10, respectively. Based on this information, the null hypothesis that X2 has no significant effect on Y should be stated as follows. Note: Y = crime rate in each city (crime per 100,000 residents); X1 = poverty rate (in %); and X2 = average income (in $1,000). a. β1 = 0 b. β2 = 0 c. β2 > 0 d. b2 = 0

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 upper critical value used to test the null hypothesis that there is no linear relationship between the two variables, X and Y at the 5% level of significance? Use our textbook statistical table to answer the question.