3.2. Instructions for the laboratory work

The sequence of laboratory work:

- Preparation of initial data obtained from the given option the teacher;

- formation in the program STATISTICA array of initial data;

- graph variation of the initial data points for each pair of "factor-review";

- the procedure pair correlation analysis and a matrix of correlation coefficients;

- identify and justify the list of characteristics of TP that can be used in the future as managers;

- formation of conclusions from the work.

3.2.1. Formation of an array of initial data

The procedure for forming an array of data is performed by the method that was described in the materials LR1.

For the array to be used in the LR3 in the window "Number of variables" are making the value 12, and "Number of cases" - are making the value 8. After appearing on-screen custom format array in his column (“Var1”“Var12”) are making data selected from tabl.3.2 according to preset option (option number LR3 data coincides with the variant data LR1).

Adding data held in the same format as in Table. 3.2. It is advisable to rename the traditional names of columns array ("Var") on the characteristics of abbreviations TP, given in section 3.4.

3.2.2. Plotting points variation of the initial data for each pair of "factor-review"

Build paired graphical dependency evaluation index performance criterion of effectiveness of TP from individual parameters according to their tabular form. For graphical data dependencies that option TP is regarded as the independent variable (X argument - odd numbers of columns in each experiment), and the estimated rate - as the dependent variable (the function Y - even numbers of columns in each experiment).

To build a graphical dependencies Estimates TP on its individual parameters TP, follow these steps (Fig.3.2): main window STATISTICA  function "Graphics"  command "2D graphics"  view of graphical construction - "Graphics of scattering."

Fig.3.2. Select a function plotting points spread

In view of this function (Fig.3.3):

entered by pressing the "Variables" from an array of initial data in position X - name of the data sample, which contains the independent variable of the experiment, and in position Y - the name of the sample with the values ​​of the dependent variable of the same experiment;

in the window “Graphic type” to leave the setting" Regular ";

enter the option "Advanced" and in the window "Adjustment" select position "Linear" (ie the program will choose the type of graph in linear approximation points spread input).

Fig.3.3. Parameter setting mode plotting

After installing the profile press OK. Schedule will be displayed in the form shown in Fig. 3.4.

Fig.3.4. View graph points spread for one of the experiments conducted univariate

These actions plotting points to spread to all six single-factor experiments.

3.2.3. Conducting procedures pair correlation analysis

To determine the coefficients of linear correlation pair perform actions as are described in the LR2: the main window of the program STATISTICA  "Statistics" ("Analysis / Descriptive statistics")  " Basic Statistics / Tables","Correlation matrices"  OK button. In the setting mode correlation analysis: "Two lists (rect. matrix)" you can choose two ways of introducing samples of variables:

a) to the left of the window to enter the name of the sample independent variable, the right part - dependent, press OK, and the window mode "Correlation matrices" - press the "Summary". The results of calculating the correlation coefficient between these variables will be displayed on the screen (Fig.3.5).

Fig.3.5. The results of calculating the correlation coefficient

Then repeat the above steps for all the other five experiments;

b) to the left and right sides of the window to enter the names of all sets of data, press OK, and then - "Summary". The program will provide results of a calculation of the correlation coefficients between all variables array of initial data in the form of a diagonal matrix (Fig.3.6 - for an array of four

samples).

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Fig.3.6. The results of calculation and choice of pairwise correlation coefficients of variables array data

Choose those correlation coefficients that interest us (correlation coefficients of variables in each experiment), can the principle of which is illustrated in Fig.3.6 (required correlation coefficients circled lines).