Question

An analysis was performed on data relating the number of weeks of experience in a job involving the wiring of electronic components and the number of components that were rejected during the past week for 12 randomly selected workers. The analysis is as follows:

Regression Analysis

r² 0.825 n 12

r -0.908 k 1

Std. Error 2.636 Dep. Var. Rejects

ANOVA table

Source SS df MS F p-value

Regression 328.1901 1 328.1901 47.24 4.34E-05

Residual 69.4766 10 6.9477

Total 397.6667 11

Regression output confidence interval

variables coefficients std. error t (df=10) p-value 95% lower 95% upper

Intercept 35.4648 1.7239 20.573 1.63E-09 31.6238 39.3059

Experience -1.3867 0.2018 -6.873 4.34E-05 -1.8363 -0.9372

What is the rate of change of number of rejects with respect to one week additional experience?

Answer 1

Answer:

Given Data

Regression Analysis

r² 0.825

n 12

r -0.908

k 1

Std. Error 2.636

Dep. Var. Rejects

Since the correlation coefficient

i.e r = -0.908

Yes this is false because there is strong negative relationship between experience and rejects produced.

What is the rate of change of number of rejects with respect to one week additional experience

The estimated regression equation is given by

= 35.4648 - 1.3867 * 1

if experience = 1 week then

= 35.4648 - 1.3867

= 34.0781

The rate of change of number of rejects with respect to one week additional experience is 34.0781.

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