Figure 3. Data on the relationship between development effort and product size in a COBOL development organization.

A least squares fit to these data yields

 

Coeff. 

SE 

t

Intercept 

1.120 

0.3024 

3.702

log10(size) 

1.049 

0.1250 

8.397

RMS 

0.194

 

 

These fitted coefficients suggest that development effort is proportional to product size; a formal test of the hypothesis, H: ß = 1, gives a t value at the .65 significance level.

The estimated intercept after fixing ß = 1 is 1.24; the resulting fit and a 95% prediction interval are overlaid on the data in Figure 3. This model predicts that it requires approximately 17 hours (= 101.24) to implement each unit of size.

Such models are used for prediction and tool validation. Consider an additional observation made of a product developed using a fourth-generation language and relational databases. Under the experimental development process, it took 710 hours to implement the product of size 183 (this point is denoted by X in Figure 3). The fitted model predicts that this product would have



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