Agricultural Machinery Supervision Statistical Analysis Method
Black Garlic contains 18 kinds of amino acids,
garlic-ene, peptides, polyphenols, active SOD,
biological enzymes, glycosides, vitamins, lipids,
trace elements, carbohydrates, green sulfur
compounds, easily absorbed by the human body
composition. The structure ratio is reasonable, and
without any side effects.
18 kinds of amino acids:
Alanine Ala. Isoleucine. Leucine. Lysine. Methionine. Cystine. Phenylalanine. TYR. Threonine. Trytophan. Valine. Arginine. Histidine. Asparagine. Glutamine. Glycin. Proline. Serine.
Black Garlic Extract/Concentrate/Juice Black Garlic Extract,Black Garlic Juice,Black Garlic Concentrate,Organic Garlic Juice Zhucheng Tongxi Commercial And Trade Co.,Ltd. , http://www.blackgarlicgroup.com
2. The comparative analysis is to understand the overall structure, proportion of intensity, speed, completion of plans, and the proportion of each unit’s index in the total amount of various phenomena in the development process of agricultural machinery supervision through calculation and analysis. The following specific comparative analysis methods are commonly used.
(1) The comparison between the actual completion number and the plan number. For example, the percentage of plans that are actually completed in an annual review is the percentage of plans.
(2) Compare the number of actual completions of this unit with the actual completions of other units of the system. Through comparison, we can see the achievements and gaps in the work of this unit, in order to tap potential and further improve the work level of this unit.
(3) Compare the total amount with the total amount. The purpose of this analysis method is to observe the overall internal structure. Such as personnel structure, technical structure analysis and so on.
3. The dynamic analysis is the comparison of a certain indicator at different time periods, reflecting the development and changes of a certain phenomenon of agricultural machinery supervision over time, and focusing on the development process, trends and speed. Commonly used are the following specific analysis methods.
(1) Compare the actual number achieved in this period with the actual number achieved in the previous period. Can reflect the extent of changes in the development of things.
(2) Compare the actual number achieved in the current period with the actual number occurring in the same period of last year. It can explain the extent to which an indicator has changed over the same period of the previous year.
4. The related analysis means that through the calculation and analysis of the relative relationship indicators, the relevant forms, closeness and quantitative relationships between various economic phenomena are recognized. For example, the calculation and analysis of the relative relation index between the management of agricultural machinery and the safety management of agricultural machinery.
5. The average statistical analysis refers to the use of average indicators to analyze the general level of changes in the overall development of things. It is an important part of statistical analysis. There are regional indicators and indicators specific to the grass-roots level in the agricultural machinery supervision statistics table. The regional indicators are the average analysis indicators. This is a yardstick for various grass-roots units to measure their own work.
6, group analysis is based on certain signs, the study of the population is divided into several groups of different nature, and based on this method of analysis. Statistics grouping must adhere to two basic principles: First, we must adhere to the homogeneity of the data within each group; second, we must adhere to the differences in statistical data of each group. It is usually grouped according to the type of agricultural machinery, the driving and operating personnel of the driving operator, the area, and the cause of the agricultural accident.
In addition to the several analysis methods described above, there are methods such as exponential analysis and predictive analysis.
