Thompson Photo Works purchased several new, highly sophisticated processing mach

Question

Thompson Photo Works purchased several new, highly sophisticated processing machines. The production department needed some guidance with respect to qualifications needed by an operator. Is age a factor? Is the length of service as an operator (in years) important? In order to explore further the factors needed to estimate performance on the new processing machines, four variables were listed:

Performance on the new machine is designated Y.

Thirty employees were selected at random. Data were collected for each, and their performances on the new machines were recorded. A few results are:

23

A. What is this equation called? 1.multiple regression equation 2.multiple standard error of estimate 3.coefficient of determination

B. How many dependent and independent variables are there? One, Two, Three, Four or Five?

C. What is the number 0.812 called? 1. Regression coefficient 2. Coefficient of determination 3. Homoscedasticity 4. Multicollinearity

D. As age increases by one year, how much does estimated performance on the new machine increase? (round answer to 3 decimal places)

E. Carl applied for a job at Photo Works. He has been in business for 5 years and scored 260 on the mechanical aptitude test. His prior on the job performance rating is 60, and he is 52 years old. Estimate his performance on the new machine (round answer to 3 decimal places.)

Thompson Photo Works purchased several new, highly sophisticated processing machines. The production department needed some guidance with respect to qualifications needed by an operator. Is age a factor? Is the length of service as an operator (in years) important? In order to explore further the factors needed to estimate performance on the new processing machines, four variables were listed:

Explanation / Answer

A.The above equation is called 1.multiple regression equation.

B.There are four independent variables (X1,X2,X3,X4) and one dependent variable (Y).

C.The number 0.812 is 1. Regression coefficient.

E.It is given that X1=5,X2=260,X3=60,X4=52, thus the performance on new machine is:

Y hat=10.2+0.4*5+0.786*260+0.812*60+0.003*52

=265.4

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