A researcher intends to determine which variables are more likely to predict public assaults against the police in Kentucky The variable represents the 2012 2016 average assault rates per 100,000 people The following correlation matrix shows the relationship between assaults against the police in the state and the 2006 2010 average homicide rates per 100,000, and other socio demographic variables at the county level in KY, based on 2010 US Census data Relationships among the independent variables are included as well Table 1 includes the Pearson correlation coefficients corresponding to bivariate relationships among five variables The unit of analysis is the county (N 120) Note The analysis is based on real data 15 points Table 1 Assaults against the police in Kentucky (N 120) Intercorrelation matrix Measures Police Assault Poverty Homicide Rate AA FHH Assault against POLICE rate 1 Poverty level 297 1 Homicide rate 176 452 1 African Americans (AA ) 316 292 040 1 Female Head of Households (FHH) 325 291 199 408 1 Identify the dependent (DV) and the independent (IV) variables Formulate the null and alternative hypotheses Note a null hypothesis should be formulated for each relationship the DV has with the selected IVs You should have 4 null hypotheses see column 1 of the correlation matrix Knowing that N 120 (the number of counties in KY), test the null hypotheses youve formulated see the critical values of Pearsons r, at the corresponding df and p 05, 2 tail test You should list the value of the critical Pearsons r Reach a statistical conclusion for each test it should be 4 tests that examines the bivariate relationship between the dependent variable and the selected independent variables and interpret your findings What characteristics appear to have those counties that registered a higher incidence of public assaults against the police in KY What variables are significantly related to assault against the police and what is the direction of the relationship What percentage of the variation in assaults against the police is explained by the percentage of female headed households at the county level Hint calculate the coefficient of determination to answer the question

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A researcher intends to determine which variables are more likely to predict public assaults against the police in Kentucky. The variable represents the 2012-2016 average

A researcher intends to determine which variables are more likely to predict public assaults against the police in Kentucky. The variable represents the 2012-2016 average assault rates per 100,000 people. The following correlation matrix shows the relationship between assaults against the police in the state and the 2006-2010 average homicide rates per 100,000, and other socio-demographic variables at the county level in KY, based on 2010 US Census data. Relationships among the independent variables are included as well. Table 1 includes the Pearson correlation coefficients corresponding to bivariate relationships among five variables. The unit of analysis is the county (N = 120). Note: The analysis is based on real data. [15 points]

Table 1. Assaults against the police in Kentucky (N = 120): Intercorrelation matrix

Measures	Police Assault	Poverty	Homicide Rate	AA%	FHH%
Assault against POLICE rate	1
Poverty level	-.297	1
Homicide rate	-.176	.452	1
% African Americans (AA%)	.316	-.292	.040	1
% Female Head of Households (FHH)	.325	.291	.199	.408	1

Identify the dependent (DV) and the independent (IV) variables
Formulate the null and alternative hypotheses [Note: a null hypothesis should be formulated for each relationship the DV has with the selected IVs]. You should have 4 null hypotheses [see column 1 of the correlation matrix].
Knowing that N = 120 (the number of counties in KY), test the null hypotheses youve formulated [see the critical values of Pearsons r, at the corresponding df and p< .05, 2-tail test]. You should list the value of the critical Pearsons r.
Reach a statistical conclusion for each test [it should be 4 tests] that examines the bivariate relationship between the dependent variable and the selected independent variables and interpret your findings. What characteristics appear to have those counties that registered a higher incidence of public assaults against the police in KY? What variables are significantly related to assault against the police and what is the direction of the relationship?
What percentage of the variation in assaults against the police is explained by the percentage of female-headed households at the county level? [Hint: calculate the coefficient of determination to answer the question].