Get Ready for the Postgraduate Entrance English Exam. Working with Texts. Часть 1. Учебное пособие

accounting depreciation and tax depreciation are almost always significantly different numbers.

II. Vocabulary Items

contra account – контрсчет

book value – реальная величина капитала, соответствующая массе выпущенных акций

capital stock – основной капитал, основные производственные фонды

deduction n – удержание

depreciation n – амортизация, изнашивание deterioration n – повреждение

direct costs – прямые издержки estimate v – оценивать, составлять смету impairment n – повреждение, ущерб indirect costs – косвенные издержки

obsolescence n – устаревание, моральный износ(оборудования) salvage value – остаточная стоимость

tangible assets – материальные (реальные) средства tax n – налог

tax benefit – налоговая льгота

wear and tear – износ основного капитала, основных средств write-down n – частичное списание

write-off n – полное списание

III. Exercises

1.Read the text.

2.Learn the vocabulary items by heart.

3.Translate the text in written form.

4.Retell the text using the following expressions and terms: wear and tear, obsolescence, impairment, capital stock, physical depreciation, manufacturing company, accounting standards bodies, write-down, write-off, the market value, original cost, asset account, contra asset account, accumulated depreciation, net book value, salvage value, to generate income, a depreciation expense, corresponding debit, expense account, asset account, adjusting journal entry.

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IV. Test IV (4)

1. Read the text again and decide which statements are true.

1.Deterioration, wear and tear of equipment, and obsolescence cause depreciation.

2.The declining-balance method is the simplest and most often used technique, in which the company estimates the “salvage value” of the asset after the length of time over which it is depreciated, and assumes the drop in the asset’s value is in equal, yearly increments over that amount of time.

3.When a company spends money for a service or anything else that isn’t a tangible asset, this expenditure is usually immediately tax deductible, and the company enjoys an immediate tax benefit.

4.Activity methods are based on time.

2. Match the words given in the left column with the words in the right column.

Final test IV

1. Match the Russian terms on the left with the English ones on the right.

2. Match the English terms on the left with the Russian ones on the right.

3. Fill in the gaps with words from the list below.

1.The process by which accounting information is collected, reported, interpreted and actioned is called … .

2.The purpose of … is mainly to show the financial position of a business at a particular point in time and to show how that business has performed over a specific period.

3.A … shows at a particular point in time what resources are owned by a business (“assets”) and what it owes to other parties (“liabilities”).

4.… were associated with productive work, and naturally rose and fell with business activity.

5.… is an estimate of the decrease in the value of an asset, caused by “wear and tear”, obsolescence, or impairment.

6.The matching principle states that costs should be matched against the … they generate.

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1.balance sheet

2.Financial Management

3.variable costs

4.financial accounting statements

5.revenues

6.depreciation

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Глава V. Статистика

Unit 1

I. Information for study

Statistics and Statistical methods

Statistics is a type of data analysis whose practice includes the planning, summarizing, and interpreting of observations of a system possibly followed by predicting or forecasting of future events based on a mathematical model of the system being observed. Statistics is a branch of applied mathematics specifically in the area of statistical theory which uses probability theory in the mathematical models. The implication of using probability theory is that statistical results can not provide definitive cause and effect relationships but can only show correlation relationships.

The basic tenet of statistics is that a population can be represented by a sample of the population when the sample is sufficiently large and when the sample is composed of a random selection of units (persons, components, or of whatever the population is composed) from the population. Statistical theory provides methods for determining how large a sample is needed to provide for statistically significant results.

There are two major types of statistics: descriptive statistics and inferential statistics. Descriptive statistics describes or summarizes the observed measurements of a system. Inferential statistics are used to infer, predict, or forecast future outcomes, tendencies, and behaviors of a system.

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Statistics are used in a wide variety of academic disciplines especially the various disciplines within the social sciences, biological sciences, and other areas of study involving complex systems. Statistics are used in business for statistical process control, quality control, marketing and other day to day activities. Statistics are used in sports to describe the expertise and abilities of sports participants. Statistics are used in government for a variety of purposes. The most well known type of statistical procedure performed by government is the census in which various statistics are collected about the national population.

Polling of a sample of a population is a typical use of statistics by political parties and the news media to determine popular opinion on particular topics. This process of sampling the population must use a process of random selection of respondents (people answering the questions of the poll) from the general population in order for the sample to have a chance of representing the general population from which it is selected.

Statistics is a partial foundation of the relatively new field of data mining, which uses a combination of statistics, pattern recognition, artificial intelligence, and other algorithms to find meaningful information in large sets of data.

Origin

The word statistics ultimately derives from the modern Latin term statisticum collegium (“council of state”) and the Italian word statista (“statesman” or “politician”). The German Statistik, first introduced by Gottfried Achenwall (1749), originally designated the analysis of data about the state. It acquired the meaning of the collection and classification of data generally in the early nineteenth century. It was introduced into English by Sir John Sinclair. Thus, the original principal purpose of statistics was data to be used by governmental and (often centralized) administrative bodies. The collection of data about states and localities continues, largely through national and international statistical services; in particular, censuses provide regular information about the population. Today, however, the use of statistics has broadened far beyond the service of a state or government, to include such areas as business, natural and social sciences, and medicine, among others.

Experimental and observational studies

A common goal for a statistical research project is to investigate causality, and in particular to draw a conclusion on the effect of changes

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in the values of predictors or independent variables on a response or dependent variable. There are two major types of causal statistical studies: experimental studies and observational studies. In both types of studies, the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types is in how the study is actually conducted.

An experimental study involves taking measurements of the system under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation may have modified the values of the measurements. In contrast, an observational study does not involve experimental manipulation. Instead data are gathered and correlations between predictors and the response are investigated.

An example of an experimental study is the famous Hawthorne studies which attempted to test changes to the working environment at the Hawthorne plant of the Western Electric Company. The researchers were interested in whether increased illumination would increase the productivity of the assembly line workers. The researchers first measured productivity in the plant then modified the illumination in an area of the plant to see if changes in illumination would affect productivity. Due to errors in experimental procedures, specifically the lack of a control group, the researchers while unable to do what they planned were able to provide the world with the Hawthorne effect.

An example of an observational study is a study which explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then perform statistical analysis. In this case, the researchers would collect observations of both smokers and non-smokers and then look at the number of cases of lung cancer in each group.

The basic steps for an experiment are to:

1.plan the research including determining information sources, research subject selection, and ethical considerations for the proposed research and method,

2.design the experiment concentrating on the system model and the interaction of independent and dependent variables,

3.summarize a collection of observations to feature their commonality by suppressing details (descriptive statistics),

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4.reach consensus about what the observations tell us about the world we observe (statistical inference),

5.document and present the results of the study.

Levels of measurement

There are four types of measurements or measurement scales used in statistics. The four types or levels of measurement (ordinal, nominal, interval, and ratio) have different degrees of usefulness in statistical research. Ratio measurements, where both a zero value and distances between different measurements are defined, provide the greatest flexibility in statistical methods that can be used for analyzing the data. Interval measurements, with meaningful distances between measurements but no meaningful zero value (such as IQ measurements or temperature measurements in degrees Celsius). Ordinal measurements have imprecise differences between consecutive values but a meaningful order to those values. Nominal measurements have no meaningful rank order among values.

II. Vocabulary Items

artificial intelligence – искусственный интеллект census n – перепись, учет численности conduct v – вести, проводить

correlation n – соотношение, взаимосвязь, корреляция data n – данные

dependent a – зависимый descriptive a – описательный

forecasting n – предсказание, прогноз independent a – независимый inferential a – логически выведенный intelligence n – сведения, информация

interpret v – толковать, интерпретировать manipulate v – управлять

observation n – наблюдение outcome n – результат pattern n – образец

polling n – опрашивание

population n – генеральная совокупность predict v – предсказывать, прогнозировать

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probability theory – теория вероятности random a – случайный

sample n – выборка set n – набор

statistics n – статистика; статистические данные summarizing n – подведение итога

tenet n – догмат, принцип variable n – переменная

III. Exercises

1.Read the text.

2.Learn the vocabulary items by heart.

3.Translate the text in written form.

4.Retell the text using the following expressions and terms: data analysis, predicting or forecasting of future events, the basic tenet of statistics, a random selection of units, descriptive statistics, inferential statistics, a sample of a population, data mining, independent variable, dependent variable, experimental studies, observational studies, levels of measurement (ordinal, nominal, interval, and ratio).

IV. Test V (1)

1. Read the text again and decide which statements are true.

1.The basic tenet of statistics is that a population can be represented by a sample of the population when the sample is sufficiently small and when the sample is composed of a random selection of units (persons, components, or of whatever the population is composed) from the population.

2.Descriptive statistics are used to infer, predict, or forecast future outcomes, tendencies, and behaviors of a system.

3.Statistics is a partial foundation which uses a combination of statistics, pattern recognition, artificial intelligence, and other algorithms to find meaningful information in large sets of data.

4.Ratio measurement provides the greatest flexibility in statistical methods that can be used for analyzing the data.

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2. Match the words given in the left column with the words in the right column.

Unit 2

I. Information for study

The Importance of Probability in Statistics

Probability

A central feature of inferential statistics is its use of information concerning a sample to make inferences about the nature of the population from which the sample is drawn. For example, the Gallup Poll used sample data to make an inference concerning the proportion of all voters who would vote for a particular presidential candidate. And Imperial Chemical Industries used sample data to make an inference concerning the true effect of a chlorinating agent on the abrasion resistance of rubber. Any conclusion based on a sample must be subject to a certain amount of uncertainty. Thus, even if ICI finds that the chlorinating agent increases abrasion resistance for 150 pieces of rubber, there is always a chance that these results are somehow a fluke and that, if the sample size were increased to 1,000 or to 10,000 the results would be reversed.

How much certainty can you attach to a particular statement about a population that is based on the results of a sample? Intuitively, you are likely to feel that the answer depends on the size of the sample. The bigger the sample, the more confidence you are likely to have in the sample results; the smaller the sample, the less confidence you are likely to have

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