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Campus Crime Rates Are Generally Lower Than the National Average;however

question 59

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Campus crime rates are generally lower than the national average;however thousands of crimes take place on college campuses daily.Cities that are notoriously dangerous would likely be undesirable locations for a college campus.A study examined the crime rates on campuses throughout the United States and whether or not they were significantly affected by surrounding cities.A regression analysis was performed to investigate which characteristics of a city,along with a few chosen demographics of a school,impacted the crime rate on a college campus.There are over 4000 colleges and universities in the United States.The study included a random sample of 129 institutions.The response variable was the number of crimes per 1000 people.Explanatory variables included the percent of married couples in the city (married) ,tuition of the university (tuition) ,average income of the city (income) ,unemployment rate of the city (unemployment) ,percent of students who belong to a fraternity or sorority (Greek) ,average age of the students at the university (age) ,and number of liquor stores in the city (liquor) .A complete analysis of the data is shown below. Campus crime rates are generally lower than the national average;however thousands of crimes take place on college campuses daily.Cities that are notoriously dangerous would likely be undesirable locations for a college campus.A study examined the crime rates on campuses throughout the United States and whether or not they were significantly affected by surrounding cities.A regression analysis was performed to investigate which characteristics of a city,along with a few chosen demographics of a school,impacted the crime rate on a college campus.There are over 4000 colleges and universities in the United States.The study included a random sample of 129 institutions.The response variable was the number of crimes per 1000 people.Explanatory variables included the percent of married couples in the city (married) ,tuition of the university (tuition) ,average income of the city (income) ,unemployment rate of the city (unemployment) ,percent of students who belong to a fraternity or sorority (Greek) ,average age of the students at the university (age) ,and number of liquor stores in the city (liquor) .A complete analysis of the data is shown below. Based on the analysis of the data with all the variables in the model,what can you conclude? What should be done next? A) The analysis is complete and all necessary assumptions are valid.Therefore,we can confidently say that none of the explanatory variables are significant predictors of crime. B) There are a large number of insignificant variables in the model.Therefore,the model should be refined.For example,remove one of the variables that was highly correlated together from the model and repeat the analysis. C) Perform an eight-way ANOVA analysis instead,with all the explanatory variables as factors. D) None of the above Campus crime rates are generally lower than the national average;however thousands of crimes take place on college campuses daily.Cities that are notoriously dangerous would likely be undesirable locations for a college campus.A study examined the crime rates on campuses throughout the United States and whether or not they were significantly affected by surrounding cities.A regression analysis was performed to investigate which characteristics of a city,along with a few chosen demographics of a school,impacted the crime rate on a college campus.There are over 4000 colleges and universities in the United States.The study included a random sample of 129 institutions.The response variable was the number of crimes per 1000 people.Explanatory variables included the percent of married couples in the city (married) ,tuition of the university (tuition) ,average income of the city (income) ,unemployment rate of the city (unemployment) ,percent of students who belong to a fraternity or sorority (Greek) ,average age of the students at the university (age) ,and number of liquor stores in the city (liquor) .A complete analysis of the data is shown below. Based on the analysis of the data with all the variables in the model,what can you conclude? What should be done next? A) The analysis is complete and all necessary assumptions are valid.Therefore,we can confidently say that none of the explanatory variables are significant predictors of crime. B) There are a large number of insignificant variables in the model.Therefore,the model should be refined.For example,remove one of the variables that was highly correlated together from the model and repeat the analysis. C) Perform an eight-way ANOVA analysis instead,with all the explanatory variables as factors. D) None of the above Campus crime rates are generally lower than the national average;however thousands of crimes take place on college campuses daily.Cities that are notoriously dangerous would likely be undesirable locations for a college campus.A study examined the crime rates on campuses throughout the United States and whether or not they were significantly affected by surrounding cities.A regression analysis was performed to investigate which characteristics of a city,along with a few chosen demographics of a school,impacted the crime rate on a college campus.There are over 4000 colleges and universities in the United States.The study included a random sample of 129 institutions.The response variable was the number of crimes per 1000 people.Explanatory variables included the percent of married couples in the city (married) ,tuition of the university (tuition) ,average income of the city (income) ,unemployment rate of the city (unemployment) ,percent of students who belong to a fraternity or sorority (Greek) ,average age of the students at the university (age) ,and number of liquor stores in the city (liquor) .A complete analysis of the data is shown below. Based on the analysis of the data with all the variables in the model,what can you conclude? What should be done next? A) The analysis is complete and all necessary assumptions are valid.Therefore,we can confidently say that none of the explanatory variables are significant predictors of crime. B) There are a large number of insignificant variables in the model.Therefore,the model should be refined.For example,remove one of the variables that was highly correlated together from the model and repeat the analysis. C) Perform an eight-way ANOVA analysis instead,with all the explanatory variables as factors. D) None of the above Campus crime rates are generally lower than the national average;however thousands of crimes take place on college campuses daily.Cities that are notoriously dangerous would likely be undesirable locations for a college campus.A study examined the crime rates on campuses throughout the United States and whether or not they were significantly affected by surrounding cities.A regression analysis was performed to investigate which characteristics of a city,along with a few chosen demographics of a school,impacted the crime rate on a college campus.There are over 4000 colleges and universities in the United States.The study included a random sample of 129 institutions.The response variable was the number of crimes per 1000 people.Explanatory variables included the percent of married couples in the city (married) ,tuition of the university (tuition) ,average income of the city (income) ,unemployment rate of the city (unemployment) ,percent of students who belong to a fraternity or sorority (Greek) ,average age of the students at the university (age) ,and number of liquor stores in the city (liquor) .A complete analysis of the data is shown below. Based on the analysis of the data with all the variables in the model,what can you conclude? What should be done next? A) The analysis is complete and all necessary assumptions are valid.Therefore,we can confidently say that none of the explanatory variables are significant predictors of crime. B) There are a large number of insignificant variables in the model.Therefore,the model should be refined.For example,remove one of the variables that was highly correlated together from the model and repeat the analysis. C) Perform an eight-way ANOVA analysis instead,with all the explanatory variables as factors. D) None of the above Campus crime rates are generally lower than the national average;however thousands of crimes take place on college campuses daily.Cities that are notoriously dangerous would likely be undesirable locations for a college campus.A study examined the crime rates on campuses throughout the United States and whether or not they were significantly affected by surrounding cities.A regression analysis was performed to investigate which characteristics of a city,along with a few chosen demographics of a school,impacted the crime rate on a college campus.There are over 4000 colleges and universities in the United States.The study included a random sample of 129 institutions.The response variable was the number of crimes per 1000 people.Explanatory variables included the percent of married couples in the city (married) ,tuition of the university (tuition) ,average income of the city (income) ,unemployment rate of the city (unemployment) ,percent of students who belong to a fraternity or sorority (Greek) ,average age of the students at the university (age) ,and number of liquor stores in the city (liquor) .A complete analysis of the data is shown below. Based on the analysis of the data with all the variables in the model,what can you conclude? What should be done next? A) The analysis is complete and all necessary assumptions are valid.Therefore,we can confidently say that none of the explanatory variables are significant predictors of crime. B) There are a large number of insignificant variables in the model.Therefore,the model should be refined.For example,remove one of the variables that was highly correlated together from the model and repeat the analysis. C) Perform an eight-way ANOVA analysis instead,with all the explanatory variables as factors. D) None of the above Campus crime rates are generally lower than the national average;however thousands of crimes take place on college campuses daily.Cities that are notoriously dangerous would likely be undesirable locations for a college campus.A study examined the crime rates on campuses throughout the United States and whether or not they were significantly affected by surrounding cities.A regression analysis was performed to investigate which characteristics of a city,along with a few chosen demographics of a school,impacted the crime rate on a college campus.There are over 4000 colleges and universities in the United States.The study included a random sample of 129 institutions.The response variable was the number of crimes per 1000 people.Explanatory variables included the percent of married couples in the city (married) ,tuition of the university (tuition) ,average income of the city (income) ,unemployment rate of the city (unemployment) ,percent of students who belong to a fraternity or sorority (Greek) ,average age of the students at the university (age) ,and number of liquor stores in the city (liquor) .A complete analysis of the data is shown below. Based on the analysis of the data with all the variables in the model,what can you conclude? What should be done next? A) The analysis is complete and all necessary assumptions are valid.Therefore,we can confidently say that none of the explanatory variables are significant predictors of crime. B) There are a large number of insignificant variables in the model.Therefore,the model should be refined.For example,remove one of the variables that was highly correlated together from the model and repeat the analysis. C) Perform an eight-way ANOVA analysis instead,with all the explanatory variables as factors. D) None of the above Based on the analysis of the data with all the variables in the model,what can you conclude? What should be done next?

Definitions:

Fortunate Fifth

Refers to the top 20% of the population in terms of income or wealth, often highlighted in discussions of economic inequality.

Privileged Position

A social or economic advantage held by a particular group or individual, allowing them access to certain benefits not widely available to others.

Business

The practice of engaging in commerce, trade, or professional activities with the aim of generating profits and sustaining operations.

Elite Democratic View

A perspective within the Democratic Party that emphasizes the role and contributions of its most influential and high-ranking members in shaping policy and governance.

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