A survey conducted by a research team was to investigate how the education level, tenure in current employment, and age, are related to annual income. A small sample employees is selected and the data is given below. Education Tenure Age Annual Income 40 124000 41 30000 44 193000 42 88000 45 140000 42 11000 18 21000 40 151000 35 124000 17 12 20 14 16 13 8 12 4 17 7 11 20 19 What.is the multiple linear regression equation for predicting Annual Income (as the response variable) from the other three variables? Note: Coefficients are rounded to nearest whole number. 寸 IN 449
A survey conducted by a research team was to investigate how the education level, tenure in current employment, and age, are related to annual income. A small sample employees is selected and the data is given below. Education Tenure Age Annual Income 40 124000 41 30000 44 193000 42 88000 45 140000 42 11000 18 21000 40 151000 35 124000 17 12 20 14 16 13 8 12 4 17 7 11 20 19 What.is the multiple linear regression equation for predicting Annual Income (as the response variable) from the other three variables? Note: Coefficients are rounded to nearest whole number. 寸 IN 449
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![What is the multiple linear regression equation for predicting Annual Income (as the
response variable) from the other three variables?
Note: Coefficients are rounded to nearest whole number.
Annual Income = -189267 + 17806 Education - 3768 Tenure + 918 Age
Annual Income = -200892 + 13834 Education - 4355 Tenure + 3204 Age
Annual Income
-199892 + 12949 Education - 1629 Tenure + 3030 Age
=
Annual Income = -179145 + 16163 Education - 4020 Tenure + 1554 Age
Annual Income = -200075 + 17498 Education + 3096 Tenure - 90 Age](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F0a08c678-100e-4106-b818-092f6da34e38%2F863dfa03-7e0a-4614-9310-06f887095e0d%2Fyaghaj_processed.jpeg&w=3840&q=75)
Transcribed Image Text:What is the multiple linear regression equation for predicting Annual Income (as the
response variable) from the other three variables?
Note: Coefficients are rounded to nearest whole number.
Annual Income = -189267 + 17806 Education - 3768 Tenure + 918 Age
Annual Income = -200892 + 13834 Education - 4355 Tenure + 3204 Age
Annual Income
-199892 + 12949 Education - 1629 Tenure + 3030 Age
=
Annual Income = -179145 + 16163 Education - 4020 Tenure + 1554 Age
Annual Income = -200075 + 17498 Education + 3096 Tenure - 90 Age
![A survey conducted by a research team was to investigate how the education level,
tenure in current employment, and age, are related to annual income. A small sample
employees is selected and the data is given below.
Education Tenure Age Annual Income
40 124000
41 30000
44 193000
42 88000
45 140000
42 11000
18 21000
17
8.
12
12
20
14
16
13
11
20
19
17
7
4
7
40 151000
35 124000
What.is the multiple linear regression equation for predicting Annual Income (as the
response variable) from the other three variables?
Note: Coefficients are rounded to nearest whole number.
4.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F0a08c678-100e-4106-b818-092f6da34e38%2F863dfa03-7e0a-4614-9310-06f887095e0d%2Frwuqm7a_processed.jpeg&w=3840&q=75)
Transcribed Image Text:A survey conducted by a research team was to investigate how the education level,
tenure in current employment, and age, are related to annual income. A small sample
employees is selected and the data is given below.
Education Tenure Age Annual Income
40 124000
41 30000
44 193000
42 88000
45 140000
42 11000
18 21000
17
8.
12
12
20
14
16
13
11
20
19
17
7
4
7
40 151000
35 124000
What.is the multiple linear regression equation for predicting Annual Income (as the
response variable) from the other three variables?
Note: Coefficients are rounded to nearest whole number.
4.
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