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

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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:

Negative Earnings

A financial situation where a company's expenses exceed its revenues, leading to a net loss in its income statement.

Prop Up Earnings

Tactics used by companies to artificially inflate or support their reported earnings per share (EPS) without a real increase in profitability.

Slightly Positive

Referring to a modestly favorable outcome or result, often used in the context of financial results or economic indicators.

Capacity Swaps

Capacity swaps involve the exchange of production capacity or output between companies, usually to meet demand or manage surplus without the exchange of monetary payment.

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