Psychologists suspect that watching violent films leads to an increase in violent criminal activity in the...

 

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Psychologists suspect that watching violent films leads to an increase in violent criminal activity in the short term. A researcher wants to test this assumption with time series observational data of 516 observations. The following is the model used by the researcher: log(assaults)t=B0+Blviol_atdt+u Where: Assault = number of violent crimes in a day viol_atd = number of viewers of violent films in a day (in a million people) The following are the results of the researcher's regression (the number in brackets under the regression coefficient is the standard error): log(assaults)t-8.23-0.007viol_atdt (0.04) (0.002) a) Are the regression results in line with the findings of the psychological experiment? Do some testing to support your answer! b) Interpret the intercept coefficient and (slope) I' of the model! c) What will happen to l'if_atd is counted in thousands of people? How much change would the daily violence count if 2.6 million people reduced the audience for violent films? d) What factors can be contained in the random error component (u)? Are these factors possibly correlated with _atdt? Do you think this simple regression model can be used to estimate the causal impact of_atd? Explain your answer! Psychologists suspect that watching violent films leads to an increase in violent criminal activity in the short term. A researcher wants to test this assumption with time series observational data of 516 observations. The following is the model used by the researcher: log(assaults)t=B0+Blviol_atdt+u Where: Assault = number of violent crimes in a day viol_atd = number of viewers of violent films in a day (in a million people) The following are the results of the researcher's regression (the number in brackets under the regression coefficient is the standard error): log(assaults)t-8.23-0.007viol_atdt (0.04) (0.002) a) Are the regression results in line with the findings of the psychological experiment? Do some testing to support your answer! b) Interpret the intercept coefficient and (slope) I' of the model! c) What will happen to l'if_atd is counted in thousands of people? How much change would the daily violence count if 2.6 million people reduced the audience for violent films? d) What factors can be contained in the random error component (u)? Are these factors possibly correlated with _atdt? Do you think this simple regression model can be used to estimate the causal impact of_atd? Explain your answer!

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