Statistical Conceptions in the Soviet Union Examined from Generally Accepted Scientific Viewpoints

Analysis of data from a mall survey in the Soviet Union, carried out by the agency responsible for the distribution of America Illustrated, strongly suggests that the data were falsified. Information about Soviet society (including the results of a number of other surveys of the Soviet population) and probability theory were used to generate a set of expected results for this survey. The actual results differed dramatically from the expected—the response rate was much too high, the sample was too young and contained too many workers, and too many people had managed to see almost all of the previous year's issues. These discrepancies, combined with the fact that the results served the interests of the Soviet officials and that it would have been easy for them to falsify the data, lead us to suspect that they did so. The conclusion discusses the conditions under which various kinds of falsification are most likely and general strategies for detecting falsification.

T X he worldwide depression after World War I revived anxiety about the ability of the capitalist system to survive future crises. European and American economists sought to improve the statistical tools with which to analyze and ameliorate cyclical fluctuations. Various institutes sprang up, notably the National Bureau of Economic Research in New York in 1920 and the Institut f?r Konjunkturforschung in Berlin in 1925.1 In the Soviet Union under the New Economic Policy (NEP, 1921-28), the Bolshevik government likewise needed statistics on agriculture, finance, trade, and industry, partly to make the case for the imminent collapse of capitalism, but primarily to repair the ravages of World War I and the Civil War and to chart a strategy of economic development to be funded primarily by meager domestic resources. The Bolshevik leadership sought to staff the agencies of the new state with technically skilled and politically committed experts from the working class and peasantry, but so few such cadres existed that it had no choice but to hire professional staff trained in the tsarist period, whose political allegiance to communism it considered doubtful. The tension between the government's preference for politically committed red cadres and its dependence on expert employees existed in every Soviet agency. In the Central Statistical Administration (TsSU), for example, many statisticians who had gathered data and analyzed

The scientist, statesman, academician Albinas Rimka (1886–1944) is famous in Lithuanian historiography as a creator of independent Lithuania. First of all, his merits as a politician and economist are to be mentioned. Albinas Rimka is considered to be the founding father of science of statistics in Lithuania in 1920–1940. In the textbooks on fundamentals of statistics and at lectures which Albinas Rimka delivered at university, the academician based statistical methods upon the main verities of high mathematics including elements of mathematical analysis, theory of probability, and mathematical statistics. In his textbooks, we can find elements of application of mathematics which were not given attention by other researchers (historians and economists) in Lithuania. The article tries to fill in the gap in research of origins of science of statistics in Lithuania with the help of the analysis of Albinas Rimka’s textbooks.

(1993). Crime and punishment in Soviet officialdom, 1965–90. Europe-Asia Studies: Vol. 45, No. 2, pp. 259-279.

This paper gives a short review of Euler’s work in the statistical sciences. During Euler’s lifetime there was a strong interest in the practical use of mathematical modelling and this increasingly encompassed the calculus of probabilities. In the middle of his life, Euler’s interest was piqued by questions involving games of chance. He also occasionally solved problems in probability theory. At the request of king Frederic II of Prussia, for example, he analysed designs for two state run lotteries. The natural applications of probability and statistics involved such questions of public policies as the prediction of population growth, or the establishment of life tables in order to predict the expenses of insurance schemes for widows and orphans. A few of Eulers texts in these areas are discussed in the paper.

The current topic may be called “statistical science”, encompassing statistical theory and its applications in science and technology. One pillar is probability theory, underpinning statistical inference and forming the basis for special models. Various types of models are distinguished. A second pillar is the design, analysis and interpretation of investigations. The discussion here touches on measurement issues, methods of analysis, detailed techniques, causation, and decision analysis. Formal theories of inference are discussed. Issues arising in the provision and use of official statistics are briefly discussed.

In the last years of the Soviet Union the role of the Gulag in Soviet history began to be discussed in a way which reflected the archives' penchant for seeking out 'positive' aspects of an horrific phenomenon. Despite the difficulties of life in the camps outlined above, the Gulag's contribution to the Soviet war economy was eulogised in official pronouncements of this time. The address given by the Soviet leader, Mikhail Gorbachev, on the forty-fifth anniversary of victory referred to those who, 'despite their own tragic fate, not sparing themselves … worked for Victory'. Similarly, the historian of the Gulag, V. N. Zemskov, wrote of camps 'packed full of people dedicated to the Communist Party and Soviet power, who during the war … asked to defend the Motherland, and the ideals of the October revolution and socialism'.1KeywordsProductive LabourLabour ShortagePrisoner ContingentMilitary ProductionTragic FateThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This chapter discusses some of the ‘internal’ problems facing the Soviet leadership in the 1980s. It will concentrate on three major areas: the problems of ruling Eastern Europe; the nationalities question; and the security of Siberia. The USSR’s economic difficulties are examined in the following chapter. These are important questions, each of which could have a major impact on the outlook for Soviet power in the years ahead. If any of these issues were to slide out of control, the consequences for political stability in the Soviet Union could be grave. Should widespread rebellion break out in Eastern Europe, or if a major nationality group rose up in revolt, or if the territorial integrity of the far flung Soviet state were threatened, then Soviet state power would be seriously undermined. On the other hand, if the Soviet multinational state continues to work without undue friction, if Siberia and Central Asia increasingly provide the economic sinews of Soviet power, and if Eastern Europe remains quiescent, then the USSR will have a sound basis of domestic power, and it will not be distracted by internal weaknesses.

Chapter 2 - Probability and Statistics

This paper has conducted a comprehensive review of more than 30 machine learning (ML) and deep learning (DL) algorithms across four main categories: supervised, unsupervised, reinforcement and deep learning. The discussion focused on the description of each algorithm, the application of mathematical foundations in their implementation, and their relevance to various practical applications. Through this analysis, the critical importance of underlying mathematical and statistical concepts, such as optimization, probability theory, and geometry, in the development of ML and DL models was highlighted A key conclusion of the paper is the diversity and adaptability of ML and DL algorithms in a wide range of fields, including computer vision, natural language processing, robotics, and medicine. This analysis underscores how rapidly the field is advancing, marked by the evolution of complex models that have transformed machine learning and adaptive capabilities.However, the work also recognizes the challenges and limitations that exist in the design and implementation of these algorithms, including overfitting, interpretability, and computational consumption. These challenges underscore the need for continued research and development to optimize and create new techniques that overcome these barriers.Looking to the future, the work suggests a focus on developing even more generative models.

As the Soviet Union moves precariously into the 1990s, the attention of Western statesmen and analysts remains fixed upon Mikhail Gorbachev's efforts to implement perestroika and glasnost at home and his still ambiguously defined new thinking abroad. Whether the topic is arms control negotiations with the West, the introduction of elements of pluralism into the long moribund Soviet political scene, or the abrupt withdrawal of Soviet power from forward vantage points in the Third World (i.e. Afghanistan), few Western observers any longer doubt that a fundamental transformation has taken place in the Soviet system. Indeed, as Western scholars increasingly acknowledge the significance of the Gorbachev revolution, it has also become apparent that the particular region most heavily influenced by this reform program has been the USSR's former East European empire. The implications of change have been most dramatic for Eastern Europe precisely because events have been propelled by both of the key elements in the Gorbachev program—the Soviet leader not only pushed glasnost and perestroika upon his East European allies (with what were probably unforeseen results), but the ultimate test of new thinking in the foreign policy realm has been the tolerant Soviet response to the collapse of Communist Party authority throughout the bloc. In this sense the movement toward liberal reform in Eastern Europe was both initiated and insulated by the dynamics of Gorbachev's own domestic and foreign reform programs. The apparent Soviet willingness to accept a reunified Germany on Western terms represents, of course, the ultimate Soviet concession along these lines. While the prospects for a peaceable transition away from communism for Eastern Europe may not be decided for some time, one more certain by-product of these developments has been the collapse of the Warsaw Treaty Organization (WTO) as a viable security system. As the institutional linchpin of the Soviet-East European relationship, the Warsaw Pact could hardly have been expected to remain unaffected by the dramatic changes sweeping bloc affairs. In many respects, the high level of Soviet-East European military integration fostered over the

The Iran-Iraq War began within nine months of the USSR’s December 1979 invasion of Afghanistan — a move which was widely interpreted in the West as a dangerous extension of Soviet power on the periphery of the Persian Gulf and which prompted a vigorous Western response symbolized by the Carter Doctrine and the creation of the Rapid Deployment Force (RDF, later reconfigured as CENTCOM).1 Eight years later, as the Gulf War winds down, Soviet forces are being withdrawn from Afghanistan under the terms of the April 1988 Geneva accords. The latter development, which raises interesting questions about how the Soviet leadership now defines security along its southern border, reflects the profound changes in Soviet policies which began following the death of Leonid Brezhnev in November 1982 and which have accelerated with the ascension to power of General Secretary Mikhail Gorbachev in March 1985.2 In his February 1986 address to the Twenty-Seventh CPSU Party Congress, Gorbachev baldly stated that Soviet foreign policy must be made to serve the ends of the state’s ambitious programme of domestic reforms (viz. perestroika). The Soviet leadership has called for a more quiescent period in international relations during which the Soviet Union can attempt to rejuvenate its declining socio-economic base. Without the successful implementation of these far-reaching domestic measures, Gorbachev warns that the USSR cannot expect to be a competitive twenty-first-century power.KeywordsIslamic RepublicDiplomatic RelationSoviet LeadershipSoviet PolicyIranian RevolutionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The Poisson distribution is a fundamental concept in probability theory and statistics. It is widely used to model the occurrence of rare events across diverse fields, including physics, biology, finance, and medicine. It offers a way to calculate the likelihood of a certain number of events occurring within a specified time period, assuming the events happen independently of one another. The Poisson distribution is commonly used to predict the outcome of random, independent events. In heavy ion-induced nuclear reactions where compound nuclei are formed under conditions of high spin and moderate excitation energy, the investigation of one or multiple neutron emissions is of particular interest. When heavy-ion reactions occur, a random number of neutrons may be released as the target becomes excited by partial or complete absorption of projectile energy, leading to the formation of a highly excited composite system. These neutrons are statistically evaporated to de-excite the compound nucleus (CN). The Poisson distribution function can thus be applied to describe the decay probability of an excited nucleus, particularly for predicting the emission of a specific number of neutrons. In this process, the excess of excitation energy over the binding energy of the released neutrons acts as the continuous variable, and the number of released neutrons serves as the discrete variable. This framework helps us quantify the likelihood of observing a given number of neutrons emitted from an excited nucleus formed in a typical nuclear reaction. In this work, the measured cross-section data for multiple neutron evaporation channels in systems such as [Formula: see text]Ho, [Formula: see text]Tm, [Formula: see text]Te, [Formula: see text]Nd, [Formula: see text]Tm, [Formula: see text]Yb and [Formula: see text]Lu reactions have been analyzed using the Poisson distribution. This approach allows all open channels to be treated simultaneously, offering a simplified yet physically meaningful alternative to more elaborate statistical models.

The authors, based on the journalistic discourse from the concluding period of perestroika, endeavor to analyze the perspectives and approaches of representatives of official government authorities as well as the emerging and increasingly influential opposition press regarding the exacerbated interethnic relations and the pathways to resolving interethnic conflicts that arose in the late 1980s. The study examines the opinions of representa-tives from opposition media concerning the causes of interethnic conflicts in the territory of the former USSR during the perestroika years, categorizing these approaches into major groups. The authors substantiate, through extensive material, that the primary source of nationalist sentiments in the USSR during 1989–1990 was the Baltic republics, where nationalists effectively managed to subordinate state structures, initiate pro-cesses of state independence formation, and disseminate nationalist propaganda with impunity. A significantly more constructive position regarding the issue of interethnic relations was adopted by the moderate liberal op-position press, which, while critically addressing the errors of Soviet leadership in national policy, nonetheless supported the reforms being implemented in the country and advocated for the preservation and renewal of the USSR. An anti-perestroika opposition emerged, whose representatives sharply criticized the national policy of the Soviet leadership, perceiving it as a deviation from Marxist-Leninist theory. Concurrently, in the RSFSR dur-ing 1987–1989, an independent opposition press, often manifesting in the form of samizdat, was formed and strengthened, reflecting viewpoints on the policies of the Communist Party of the Soviet Union (CPSU) and the state concerning interethnic relations that starkly contrasted with official narratives.

The paper reports on a two-year investigation into the feasibility of allocating three weeks of an undergraduate calculus-based probability course to statistics. This brief introduction to statistics would take the place of a course, thus constituting the students' only exposure to statistical science. At first glance, the request seemed quite reasonable. Statistical inference is based on probability, and statistical inference could be presented as an application of probability. Besides introducing some statistical concepts, it was hoped to enhance understanding of probability by highlighting this connection. However, it was not possible for the students to learn anything meaningful about statistical science in three weeks. In addition, any enhancements to the learning of probability were not significant enough to warrant the omission of material from that course.