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For prediction of future events, there exist a number of methods usable in managerial practice. Decision on which of them should be used in a particular situation depends not only on the amount and quality of input information, but also on a subjective managerial judgement. Paper performs a practical application and consequent comparison of results of two selected methods, which are statistical method and deductive method. Both methods were used for predicting wine exports and imports in (from) the Czech Republic. Prediction was done in 2003 and it related to the economic years 2003/2004, 2004/2005, 2005/2006, and 2006/2007, within which it was compared with the real values of the given indicators.
Within the deductive methods there were characterized the most important factors of external environment including the most important influence according to authors' opinion, which was the integration of the Czech Republic into the EU from 1^st May, 2004. On the contrary, the statistical method of time-series analysis did not regard the integration, which is comes out of its principle. Statistics only calculates based on data from the past, and cannot incorporate the influence of irregular future conditions, just as the EU integration. Because of this the prediction based on deductive method was more optimistic and more precise in terms of its difference from real development in the given field.

The paper evaluates drinking water quality on selected dairy farms on the territory of the Czech Republic. The drinking water samples were collected in the farm milk storage rooms of 30 farms with subsequently made analyses. The pre - selected chemical and microbiological indicators were stated according to the regulation No. 252/2004 Coll. (pH, conductivity, chemical oxygen demand, colour, turbidity, Fe, ammonia ions, nitrites, nitrates, colony count growing at 36 °C, colony count growing at 22 °C, coliform bacteria, Escherichia coli, Ca, Mg, Na, K, Zn, Cu, Mn, Pb, Cr and Ni). The statistical evaluation was performed in the obtained data file and these data were compared with the limit values given by the regulation. The nitrate content ranged between 1 and 40.7 mg L^-1 with an average of 15.6 mg L^-1. The pH values varied from 5.71 to 8. The chloride concentration geometrical means was 7.57 mg L^-1. The Ca average concentration 58.5 mg L^-1 was in the middle of the recommended interval 40-80 mg L^-1. The geometric means in Mg content was 7.9 mg L^-1 being under the recommended value 20-30 mg L^-1. The Cu, Pb, Cr and Ni limit values were not exceeded. The limit values in microbiological analyses were exceeded 18x in coliform bacteria, 10x in enterococci, 5x in Escherichia coli. The microbiological colonies growing at 36 °C exceeded limit 9x, those growing at 22 °C 5x.
Further, differences are compared between the organic and conventional farms, and between farms producing milk in different type of LFAs (less favourable areas) and farms not included in these areas. The difference found out between the chloride concentrations in organic (6.56 mg L^-1) and conventional farms (18.2 mg L^-1; p < 0.05) was statistically significant. Locality or altitude, where a given far is situated, were another classifying criterion. A significant dependence was only found out in nitrate content, which decreased (p < 0.05) with increasing altitude (the correlation coefficient value -0.39). It can correspond with the soil use decrease - a lesser fertilization intensity. Statistically significant differences were found out in hardness value as well as in Ca, Mg contents connected with that in all reference criterions. The hardness was clearly lower (1.13 mmol L^-1) in organic farms as compared with concentration 2.27 mmol L^-1 in conventional ones. It is, however, only a supplementary indicator according to the respective regulation. No statistical significance was found among microbiological finding values in any case.

The IASB project "Business Combinations" started in 2001. The increase of financial statements quality and international harmonization of business combinations recording were main objectives of this project. The project was divided into two phases. IFRS 3 (2004) Business Combinations" which replaced former IAS 22 was the result of the first phase. Partial harmonization of recording and financial reporting of business combination in Europe and in the USA was the main objective of IFRS 3 (2004). IFRS 3 (2004) is based on SFAS 141 (2001). SFAS 141 (2001) was developed in 2001 and replaced APB (Accounting Principles Board) Opinion No. 16 Business Combinations and SFAS 38. There is the pooling interest method forbidden and only the purchase method is allowed for all kinds of business combinations. Based on the comparison of both methodical approaches to business combinations are demonstrated reasons for refusing of pooling interest method. The second phase is aimed at purchase method application and new methodical approaches to business combination recording and it is the objective of the conclusion of this paper.

Essential part of raw milk component measurement is indirect infraanalyse. The checking of time measurement stability is important there. The preparation of pilot samples was described. Information about deep frozen milk pilot sample stability are sporadic. Aim of this work was to verify the stability of long-term stored and deep frozen pilot samples (FPSs). Pilot samples were frozen in liquid nitrogen bath -196 °C and after that stored at -21 °C for one month (A) and more months (B) till analyse. The pilot samples were measured by CombiFoss 6000: fat F (%); protein CP (%); lactose L (%); casein C (%); solid non fat SNF (%); urea U (mg/100ml); somatic cell count SCC (ths./ml). In the short-term (A) experiment the impact of freezing on pilot milk samples was relatively small, in the framework of acceptable value of repeatability (±0.02 %) for components. The stability of values of FPSs was better according to standard deviations for important F evaluation in H (Holstein) breed samples. The repeatability of values of FPSs in the time was very good for other components. The repeatability was better for SCC in J (Jersey) breed samples (±16.5 thousands/ml). That is why the higher variability (±30.1 thousands/ml) in H sample is visible less sceptically. The apparent result trends were not observable in the repeatability development of important milk indicators in FPSs. The mild trend was only in CP, but this trend covered absolutely very small shift (variation range). There are only oscillations, which are similar between J and H samples. It is possible to attribute these oscillations rather to instrument effects than to sample effects. The oscilations were markedly higher in the long-term (B) experiment. Between J and H samples the oscilations were very similar in curves F and L. It is also possible to attribute them more to instrumental effects. The repeatability values (standard deviations sd) of FPSs were mostly lower than ±0.06 %. It is acceptable for result agreement between indirect and reference method. Relevant sd varied from ±0.025 % for L to ±0.059 % for F (in J breed) with exception CP ±0.085 % in J sample. Also B procedure was shown as applicable for instrumental sability control in half year period. In practice the one reference value for concrete FPS is valid from one to next calibration. Persistent trend in repeatability of FPSs can indicate an inadequate instrumental drift. The applied FPS procedure is usable for stability control of instrumental measurement in milk laboratories.