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Average and limiting errors of small sample are defined under formulas: where
Example 6.1. Sample of 10 units of production from 100 let out is made on
Under the resulted data it is possible to define a share of defective production in
To sample: W = 0,2.
Sample dispersion?? = W * (1 - W) = 0,2 * 0,8 = 0,16.
Average quadratic deviation (? =) = 0,4.
Then an average error of small sample
Hence, a share of defective production in a general totality:
it = 0,2 0,133.
Under the table of distribution of Stjudenta (tables are available in editions on
To the mathematical statistics) it is established that probability of reception
Defective production on new equipment S (t) = 0, 858.
Statistical methods can be useful, when it is required to define
Expected results at modification or improvements in
For this purpose it is necessary to spend a series of tests and to analyse them
Results. Average values of parametres of advanced products
Are compared to parametres of the control party made in the former
Calculation can be executed with application of average linear deviations.
At an estimation of degree of improvement of technics it is important to answer a question,
How much new technics is more progressive also what particularly effect will receive
The consumer from its use.
Calculation of advantages of new technics can start with following preconditions:
1. Dimensions of got technics and replaced are compared:
R1 And R0 - accordingly length of the new and replaced car;
it1 And it0 - width of the new and replaced car;
it1 And it0 - height of the new and replaced car.
2. Capacity of the new and replaced car is compared:
V1 And V0 - capacity of the new and replaced car;
W1 And W0 - productivity of the new and replaced car.
3. It is useful to compare and labour input of service:
it1 And it0 - a service zone on the new and old equipment.
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