For a sample of 41 New England cities, a sociologist studies the crime rate in each city (crimes per 100,000 residents) as a function of its poverty rate (in %) and its median income (in $1,000s). A portion of the regression results are shown in the following table. |
ANOVA | df | SS | MS | F | Significance F |
Regression | 2 | 3,534,820 | 1,767,410 | 11.18263 | 3.1E-04 |
Residual | 26 | 4,109,289 | 158,049.6 | ||
Total | 28 | 7,644,109 | |||
a. |
Calculate the standard error of the estimate. (Round your answer to 2 decimal places.) |
sese |
b-1. |
What proportion of the sample variation in crime rate is explained by the variability in the explanatory variables? (Round your answer to 4 decimal places.) |
Explained proportion |
b-2. |
What proportion is unexplained? (Round your answer to 4 decimal places.) |
Unexplained proportion |
For a sample of 41 New England cities, a sociologist studies the crime rate in each...
For a sample of 29 New England cities, a sociologist studies the crime rate in each city (crimes per 100,000 residents) as a function of its poverty rate (in %) and its median income (in $1,000s). He finds that SSE = 4,133,564 and SST = 7,676,478. a. Calculate the standard error of the estimate. b-1. What proportion of the sample variation in crime rate is explained by the variability in the explanatory variables? b-2. What proportion is unexplained?
For a sample of 20 New England cities, a sociologist studies the crime rate in each city (crimes per 100,000 residents) as a function of its poverty rate (in %) and its median income (in $1,000s). A portion of the regression results is shown in the accompanying table. Use Table 2 and Table 4. ANOVA df SS MS F Significance F Regression 2 2,517.3 1,258.6 7.49E-01 Residual 17 72,837.53 4,284.56 Total 19 75,354.80 Coefficients...
For a sample of 20 New England cities, a sociologist studies the crime rate in each city (crimes per 100,000 residents) as a function of its poverty rate (in %) and its median income (in $1,000s). A portion of the regression results is as follows. [You may find it useful to reference the t table.) F 0.05 ANOVA Regression Residual Total M S 229.2 4,464.56 Significance F 0.950 df SS 2 458.3 17 75,897.54 1976,355.9 Intercept Poverty Income Coefficients 754.4596...
Data were gathered from a simple random sample of cities. The variables are Violent Crime (crimes per 100,000 population), Police Officer Wage (mean $/hr), and Graduation Rate (%). The accompanying table shows a multiple regression model for the variables. Complete parts (a) through (d). Data were gathered from a simple random sample of cities. The variables are Violent Crime (crimes per 100,000 population), Police Officer Wage (mean S/hr), and Graduation Rate (%). The accompanying table shows a multiple regression model...
19. A sociologist examines the relationship between the poverty rate and several socioeconomic factors. For the 50 states and the District of Columbia (n = 51), he collects data on the poverty rate (y, in %), the percent of the population with at least a high school education (x1), median income (x2, in $1000s), and the mortality rate per 1,000 residents (x3). He estimates the following model as y = β0 + β1Education + β2Income + β3Mortality + ε. The...
A random sample of n1 = 10 regions in New England gave the following violent crime rates (per million population). x1: New England Crime Rate 3.0 3.1 4.0 3.9 3.3 4.1 1.8 4.8 2.9 3.1 Another random sample of n2 = 12 regions in the Rocky Mountain states gave the following violent crime rates (per million population). x2: Rocky Mountain Crime Rate 3.9 4.1 4.8 5.3 3.3 4.8 3.5 2.4 3.1 3.5 5.2 2.8 Assume that the crime rate distribution...
A random sample of n1 = 10 regions in New England gave the following violent crime rates (per million population). x1: New England Crime Rate 3.3 3.7 4.2 3.9 3.3 4.1 1.8 4.8 2.9 3.1 Another random sample of n2 = 12 regions in the Rocky Mountain states gave the following violent crime rates (per million population). x2: Rocky Mountain Crime Rate 3.7 4.1 4.7 5.5 3.3 4.8 3.5 2.4 3.1 3.5 5.2 2.8 Assume that the crime rate distribution...
A random sample of n1 = 10 regions in New England gave the following violent crime rates (per million population). x1: New England Crime Rate 3.5 3.9 4.0 4.1 3.3 4.1 1.8 4.8 2.9 3.1 Another random sample of n2 = 12 regions in the Rocky Mountain states gave the following violent crime rates (per million population). x2: Rocky Mountain Crime Rate 3.9 4.3 4.5 5.3 3.3 4.8 3.5 2.4 3.1 3.5 5.2 2.8 Assume that the crime rate distribution...
Sociology/Criminology/Economics: Records comparing unemployment rates and property crime rates (per 1,000) were gathered in a state for the years 1975 - 2005 (n = 31). Below is the scatterplot, regression line, and corresponding statistics for these 31 years. Property Crime -vs- Unemployment x = Unemployment Rate (in %) y = Property Crime Rate (in crimes per 1,000 people) correlation coefficient: r = 0.8140 regression equation: ŷ = 2.59x + 28.8 sample size: n = 31 Answer the following questions...
A random sample of n1 = 10 regions in New England gave the following violent crime rates (per million population). x1: New England Crime Rate 3.3 3.7 4.0 3.9 3.3 4.1 1.8 4.8 2.9 3.1 Another random sample of n2 = 12 regions in the Rocky Mountain states gave the following violent crime rates (per million population). x2: Rocky Mountain Crime Rate 3.5 4.1 4.5 5.1 3.3 4.8 3.5 2.4 3.1 3.5 5.2 2.8 Assume that the crime rate distribution is approximately...