Based on the data obtained. Comprehensive statistical processing of experimental data. Categories of the population and census

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Based on the data obtained, it can be concluded that the company's balance sheet is not liquid. In 2010 and 2009, only a third inequality is performed, whereas in 2008 the first and third. The liquidity of the balance is defined as the degree of coverage of the enterprise's obligations by its assets, the transformation of which in monetary form corresponds to the maturity date of obligations. In fact, the enterprise is defective in the near future.

Short-term commitments can not be repaid. As you can see, the organization is not able to be calculated in its most urgent obligations with the help of the most liquid assets and, in case of such a need, will have to use other types of assets or borrowed funds. The lack of funds in the first and second groups of assets is compensated by an excess of them in the third and fourth categories. But in the actual payment situation, less liquid assets cannot replace more liquid.

In the reporting year, the company's balance sheet is also notable. It is necessary to take a number of measures to strengthen financial state Enterprises and improving its solvency.

But such a situation is characteristic of most enterprises and is still actually nothing. To clarify the situation with solvency calculated special coefficientswhich are then compared with the installed regulatory values and are considered in the dynamics to establish the pattern of development. Calculation and analysis of these indicators is presented in Table 11.

Table 11 - Relative indicators The solvency of MU BGPATP for 2008-2010.

The dynamics of the company's solvency coefficients reveals a tendency to reduce liquidity during the entire study period.

The normative value corresponds only to the magnitude of the absolute liquidity coefficient in 2008 - 0.56. The absolute liquidity ratio is the most stringent solvency indicator. Its value in the reporting year is extremely small - 0.01, which is 0.55 less than in 2008.

The coefficient of urgent or fast liquidity does not correspond to the recommended value throughout the period of the study, while it is constantly decreasing. The value of this indicator in 2010 is 0.04, which is 0.54 less than the same value of 2008.

The current liquidity ratio is a generalizing indicator of the company's solvency, it is most interesting to potential investors and creditors. The value of the current liquidity ratio does not correspond to the recommended and demonstrates a tendency to decline in comparison with 2008, however, in 2010 the value of the indicator is slightly more than in 2008 - by 0.02.

Estimated financial sustainability Companies, having calculated the adequacy of working capital for financing stocks and costs of the company.

Based on the data of Table 12, it can be seen that the enterprise MU BGPATP is in a difficult financial situation. Throughout the period of research, the enterprise traces a lack of own current means (SOS). The company practically does not use long-term lending to form working capital. As can be seen from the table to attract funds in large volumes used short-term loans and loans.

Consider an example of how it is possible on the basis of the resulting empirical data to estimate the distribution parameters of a random variable. Let us have the results of the assessment of 20 men and 20 women on the Femnost scale - the masculinity of the MMRI questionnaire (Table 1.1).

Table 1.1.

Results of the feminidity estimate - masculinity (in ascending order)

Assessment of mathematical expectation But the experimental data

We will perform an assessment of the mathematical expectation according to the experiment. For a start, let's see how you can "manually" to evaluate the magnitude of the expectation for sampling men and women. Recall that in this case we have three options.

• 1. Assessment of average arithmetic. In order to use this opportunity to assess the mathematical expectation, first of all it is necessary to calculate the sums of all test points separately for sampling men and women. The result is as follows: total amount Points for men amounted to 724, for women - 586. Now the amounts received must be divided into sample size. In our case, men's, and women's samples contain 20 people. Thus, using formula (1.2), we obtain that the assessment of the mathematical expectation for the sample of men is 36.2 points, for the sample of women - 29.3 points.
• 2. Distribution Fashion Evaluation. Recall that fashion is called the most common meaning. In order to evaluate it, we will build a frequency distribution of test points for two samples. The results of such calculations are presented in Table. 1.2, where all the scores scored by the subjects are indicated, as well as the number of tests - men and women - who scored the corresponding number of points. The same data can be submitted more clearly as histograms (Fig. 1.3). The histogram reflects the relationship between the observed values \u200b\u200bof the random variable and the frequency of their manifestation. Directly observed values \u200b\u200bare usually postponed along the horizontal axis (abscissa axis), the frequencies of their manifestation are vertical (ordinate axis).

Table 1.2.

Distribution of childbirth scored points - masculinity in groups of men and women

Thus, the presented data suggests that in the group of men, three meanings are most common, three times: 30, 31 and 41 points. Thus, in this group, we do not detect distribution modes. In a group of women, one value occurs more often than others - 33 points. This is a fashion distribution. As we see, this value is somewhat different from what was obtained when calculating the average arithmetic, which turned out to be 29.3.

Fig. 13.

3. Median assessment. In order to evaluate the median of the distribution in two samples, it is necessary first of all to streamline the data we received ascending. In tab. 1.1 Data is presented in this way. Since we have 20 subjects in each group, the middle of the variational series, ordered in ascending or descending, will have to be 10-11 subjects: because until the 10th subject turns out to be exactly 9 subjects with smaller or equal scores and after the 11th test remains Exactly 9 subjects with large or equal scores. Squeeze nine lines from the bottom and nine rows from above, you will find that both in the male, and in the women's samples, the tests, which appeared on the 10-11st places show the same results: men are 36 points, women - 31 points.

Thus, the median value of feminidity - masculinity in the male sample almost corresponds to the value of the average arithmetic, whereas for the female sample we detect a value that it turns out to be a little more than previously medium-sized arithmetic, but slightly less than previously found the distribution mod previously, actually located between these values.

The same actions can be performed using a computer. In the simplest case, any spreadsheet program can be used for calculations, such as, for example, MS. Excel from office package corporation Microsoft. or its analogues in other office packages. To estimate the average arithmetic, it will be necessary to take advantage of the function of the SRVNA. It returns the average value (arithmetic arithmetic) arguments. For example, if the range A1: A20 contains numbers, formula \u003d CPNPHOV (A1: A20) Returns the average value of these numbers. To calculate the fashion and medians, it is necessary to use the functions of the Fashion and Median accordingly. The spreadsheets also provide fairly developed opportunities for building consolidated tables and histograms.

More effectively allow the necessary computing special statistical programs. So, a well-known program statistical analysis SPSS Statistics, B. lately Developed and supported by the company IBM. For OS Windows, Macos. and Linux, Contains the descriptive statistics module. It can be found in the "Analysis" menu. Similar features represent other statistical packages, the most powerful of which seems to be a packet of statistical analysis. Statistic A. Companies Statsoft. Inc.

Consider how you can estimate the mathematical expectation of the received data and build their frequency distribution using a statistical package IBM. SPSS Statistics (it is assumed that at our disposal there is a Russian edition of this program for the environment Windows ).

First you need to properly prepare the data file. To do this, run the program, go to the "Variables" tab and enter the names of all the studied variables in the first column. In our case, it can be variable "men" and "women" (Fig. 1.4), although in general it is better to create two variables: "floor" and "feminosis" and further use filters to select suitable for data analysis.

Fig. 1.4. Creating variables for analysis of data on feminost - masculinity inIBM SPSS Statistics

Then go to the "Data" tab and enter the measurement results available we have (Fig. 1.5).

To calculate the average arithmetic, mods and medians, you must select the "Frequency" menu item in the descriptive statistics module, in the window that appears - variables for analysis, then press the "Statistics" button. In the newly appeared window, choose the "average", "median" and "fashion" (Fig. 1.6).

To build histograms in the "Frequency" window, select the "Chart" item (Fig. 1.7), in the window that appears, select the item "Histograms". If necessary, you can note the checkbox "show the histogram of a normal curve". In this case, it will be possible to compare the existing frequency distribution with theoretically possible normal distribution.

It is assumed that the Russian version is used MS. Office 2013.

Thinking about the 2010 census, I unwittingly ask for a question: "What exactly are the census? Is it possible to calculate citizens?" As I later found out, this event has much more goals. And it was about them that I would like to talk.

What is a census of the population and for which it is carried out

First of all, the census of the population is a single process that includes a collection, generalization, analysis and publication of demographic, social and economic data of the population. Census of the population can relate both to all residents of the country and to residents of individual regions.

In general, the census allows you to monitor migration processes and demographic changes. In addition, they are the leading source of state information resources. The census helps to follow the life in the country.

Categories of the population and census

There are two types of census: software and urgent.

In the first case, a full-fledged census is carried out, which includes a number of questions to the polled persons (it is about it that we think when I hear the definition itself).

But the urgent census is carried out in a limited time (usually from two to eleven days). It is very clear and short programoperational work.

• cash population. Combines all people who are at the time of the census are on the surveyed territory (plus the temporary population);
• legal population. Population, which is legally enshrined in a specific territory;
• and permanent population. These are those who have permanent accommodation On the Territory Survey (more than 6 or 12 months live there).

Now the questionnaire method is used in Russia (the census sheet is filled in the process of personal negotiations with the rewrite person). But there are two more methods that are actively used in foreign countries (the method of self-conducting and mixed method), which differ in some independence.

It is impossible not to mention that the nearest census in our country will be held in 2020. It is assumed that it will be possible on the Internet.

Short-term prediction of passenger traffic

Based on statistical data obtained

Empirical path

Nefedov V.V., Russian M.V.

Feature of private passenger traffic (PP) in a number of Russian cities

is an low level Their organizations. This is due to unordered

planning routes of passenger motor vehicles mainly in those areas of the street-road network (UDS), on which mass passenger traffic is concentrated. Due to the increase in the level of motorization and an increase in the mobility of the population against the background of the insufficient rates of UDS development, the problem of optimizing PP, aimed at the dynamic adaptation of them to constantly changing conditions. Special attention In this issue, the prediction of passenger traffic should be predicted by hours and days of the week, as well as prediction of road conditions.

IN this moment Most passenger sector do not have reliable information about passenger transported by day. This causes certain difficulties in planning the schedule of motion, because It is not known how many buses can be needed for transportation. The solution to this problem is the short-term prediction of the passenger traffic, which will most likely consider the route workload for the near future and as a result, adjust the number of buses on the line.

To automatically determine the number of passengers transported by the unit of urban transport, there are a variety of ways. Consider the most common of them.

1) A contact-turnstip method involves to calculate the transported passengers using the installation in the cabin of the bus special turnstiles.

There is the possibility of combining the fare systems with them. The advantage of such a system is a great accuracy of counting. The disadvantages include the difficulty of filling the cabin, as the landing will be carried out through the front door.

2) The method of counting passengers using sensors made in the form of steps. They are installed at the bus entrance in the form of special plates that react to pressing. If there are two steps on the bus, it is possible to establish two sensors to count the incoming and outgoing passengers. The disadvantage of such a system is the mechanical impact of passengers on sensors, which leads to their rapid wear.

3) The method of counting passengers using infrared sensors. They are active and passive type. In practice, it is recommended to use devices that include both types of sensors. Accuracy of counting varies from 70% to 95% depending on the selection of the manufacturer. There is the possibility of accounting for incoming and coming passengers.

4) A method for counting passengers using sensors that allow you to receive a 3D image of space. The principle of operation lies in from

- & nbsp- & nbsp-

Analyzing the above-described methods of counting passenger traffic, it can be concluded that infrared sensors are most suitable for the forecasting task, since they have permissible counting accuracy sufficient to estimate the volume of traffic, and are also not subject to mechanical effects and have a fairly low price.

Based on the received statistical data, it is possible to judge the capacity, the tension of the passenger traffic in separate parts of the route or in general by its length, the volume of transportation. Graphically passenger traffic are depicted in the form of EPUR (Fig. 1, 2, 3). Where along the axis of the ordinates, their values \u200b\u200bare postponed, and on the abscissa axis discrete time, the days of the week, the months of the year, the rigorous length of the route and indicates the direction of movement.

- & nbsp- & nbsp-

Figure 3 - The distribution of the passenger traffic on the length of the route from Epur can be seen that the city passenger transportation is characterized by sharp fluctuations in passenger traffic on the clock of the day (increase during the hours of travel of the population and from work and decrease in the morning, day and evening "non-peak"

clock), as well as weeks of the week (in the prehending days, passenger traffic increases, and on weekly decreases).

The development of a short-term forecasting algorithm for passenger traffic is associated with many factors that are formed both under the influence of causing ties and due to uncertainty. The latter complicate the task and require functional and probabilically statistical methods in the complex to obtain specific solutions. The short-term () prediction task is to determine the value of the passenger traffic (), ... if the values \u200b\u200b() (), ..., () and the values \u200b\u200bof the factors affect the projected flow rate at the moments, ..., and at the moments.

Imagine these factors in the form of a matrix | |:

| | ||, | | Where is a factor that determines the magnitude of the passenger traffic in one hour of the day is a month. Values \u200b\u200bhave the following values:

l - 1, 2, ..., 30, 31;

1, 2, …, 11, 12;

The composition of the source factors includes:

reflects an hour of the day.

sign like a day. The following coding system was adopted in relation to this factor: 1 - after-vacation and aftermaths, 2 - full working days of the week, 3 - weekends, 4 - Saturday, 5 - holidays, 6- Sunday, 7 - Prechange days, 8 - holidays .

The sign of the month is encoded as follows: 1 - January, February, March, 2 April, May, 3 - September, October, 4 - November, December, 5 -Iun, 6 - July, August 7 - August.

Sign of decade within a month. Codes: 1 - Days of the first decade, 2 days of the second decade, 3 days the third decade.

Sign of novelty information. The values \u200b\u200bare encoded in such a way as they approaches the forecast situation as approximation.

The average temperature of the air for the day, within the forecast day for 24 hours.

The same for the day, spaced for 48 hours.

the average air temperature in the forecast day.

accordingly, precipitation for the day, subject to the forecasts for 24 and 48 hours.

The amount of precipitation in centimeters for forecast days.

the cloud rate for the day under consideration in points.

If these situations relate to the same year, the basic value of the flow of passengers is determined by the formula:

- & nbsp- & nbsp-

The use of the considered formula allows an effective short-term forecast. However, the presence of random factors such as emergencies, an unpredictable change in the nature of the population, forecasting errors, a small number of factors taken into account in the calculations, lead to the need to take into account the random component.

Based on statistical data and forecast, when taking into account all of the above factors for bus route No. 94 of Rostov, the following passenger traffic diagram (Fig.

- & nbsp- & nbsp-

Figure 4 - Passenger traffic diagram

The number of buses for each hour is determined according to the expression:

- & nbsp- & nbsp-

Figure 5 - Diagram of the release of buses on the line by hours of the day the interval of movement, like the number of buses on the line, changes by the hour of movement depending on the magnitude of passenger traffic and is determined by addiction:

Thus, these methods for calculating the number of passengers transported by the unit of urban passenger transport will receive objective data on the volumes of passenger traffic on transport. This allows you to judge the real transportation of transport by passengers, as well as after the accumulation of statistics to conduct an effective forecast of the demand for transportation. Availability of information on the filling of the cabin along with the current location of transport on the route will make it possible to drastically change the approach to dispatch controlBy moving on the control of the interval at the final stop to the dynamic change in the schedule for emergency changes in road conditions and the demand for transportation.

BIBLIOGRAPHY

1. Automation and telemechanics. 2003, vol. 11. P. 3-47.

2. P Avdin N.V., not her V.Ya. Passenger traffic prediction (technique,