Question: use the data shown here ^ please show work Dr. Lillian Fok, a New Orleans psychologist, specializes in treating patients who are agoraphobic (i.e., afraid

use the data shown here ^ please show work Dr.use the data shown here ^

use the data shown here ^ please show work Dr.please show work

Dr. Lillian Fok, a New Orleans psychologist, specializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how many patients Dr. Fok has seen each year for the past 10 years. It also indicates what the robbery rate was in New Orleans during the same year: 1 36 2 32 3 39 4 40 5 41 6 56 7 62 8 55 9 59 10 61 Year Number of Patients Robbery Rate per 1,000 Population 57.8 61.1 73.0 76.1 81.5 89.0 101.1 94.2 104.1 116.2 The simple linear regression equation that shows the best relationship between the number of patients and year is (round your responses to three decimal places): where y = Dependent Variable and x = Independent Variable Dr. Lillian Fok, a New Orleans psychologist, specializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how many patients Dr. Fok has seen each year for the past 10 years. It also indicates what the robbery rate was in New Orleans during the same year 2 3 4 5 7 8 9 10 Year Number of Patients Robbery Rate per 1,000 Population The simple linear regression equation that shows the best relationship between the number of patients and year is (round your responses to three decimal places): = where y = Dependent Variable and x = Independent Variable. Using linear regression, the number of patients Dr. Fok will see in year 11 = patients (round your response to two decimal places). Using linear regression, the number of patients Dr. Fok will see in year 12 = patients (round your response to two decimal places). The coefficient of determination for the linear regression model is 0.8569. This shows that there is a relationship between the "Number of Patients" and "Year." strong not so strong

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