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 alternative hypothesis that X1 has 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. β1 ≠ 0 d. β1 > 0

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).

Compared to your hometown, how do you think the crime rate in Melbourne measures up?

A local city council’s study found that the correlation between number of liquor stores in a neighborhood and neighborhood crime rates across all city neighborhoods was r = 0.88.Which one of the following statements is true? As the number of liquor stores increase the crime rate will increase in that neighborhood. Closing liquor stores in a neighborhood will help to reduce the crime rate of that neighborhood. Population is a possible lurking variable in this scenario, since areas that are more densely populated are more likely to have higher crime rates. There is a pretty strong positive linear relationship between number of liquor stores and crime rates.

Distribution of criminal activity by category of crime for country x in 1990 and projected for 2000.Criminal population : 10 million