Academic literature on the topic 'Statistik 1980-1990'

The article is devoted to the analysis of the location of the main ethnic groups of European origin in the United States. Being immigrants descendants, the US population has a different ethnic origin. To date, the majority of US residents are the descendants of European immigrants. On the example of the five most numerous ethnic groups of Americans of European origin — the British, Germans, Irish, French, Italians — the spatial changes of their distribution on the US territory in the period from 1980 to 2015 are considered. The ethnic assimilation processes of various ethnic groups in the American «melting pot» occur with different intensity. But the ethnic identity changing rate depends not only on a particular ethnic group membership, but also on the characteristics of its spatial localization. Among the five ethnic groups in question, over the past 35 years, the number of Americans of English and French origin has fallen most dramatically. The number of «Italians» over the same period has increased by more than 40 %. The appearance in 1990 in the US Census Bureau statistic data a new ethnic category — «Americans», which has a distinct spatial localization, has become an important indicator of the European ethnic groups assimilation process speed and direction in the United States.

In connection with the 100th anniversary of the Republic of Estonia, it is proper and pertinent to compose synopsis of infractions of law (criminal activity) committed in those years. Since 2003, the rather complicated but most rewarding work has been the responsibility of Ministry of Justice, which also releases publications on criminal activity. Svinot Igaunijas valsts simtgadi, nozīmīga ir arī šī laika perioda likumpārkāpumu (noziedzības) analīze. Neviena statiska nav pilnīgi precīza, tomēr tā dod iespēju atspoguļot pašu būtiskāko. Noziedzības statisku valstī ietekmē normatīvās regulācijas izmaiņas. Igaunijas statistikā laika periodā no 1900. līdz 2018. gadam ir t.s. “baltie plankumi” (piemēram, par 1939.–1944. gadu). Statistikas analīze parāda, ka padomju laika periodā (1950.–1980. gadā) noziedzība bija vairākas reizes zemāka nekā 1919.–1938. gadā un pēc Igaunijas valstiskās neatkarības atjaunošanas. Slepkavību analīze rāda, ka tās visvairāk tika reģistrētas 1990.–1998. gadā. Ieslodzīto skaits padomju laika periodā bija augsts, bet neatkarības gados tas pakāpeniski samazinās. Bet mainās noziegumu struktūra. Igaunijas noziedzības struktūrā pēdējos gados vairāk tiek reģistrēti noziegumi, kas ir saistīti ar narkotiskām vielām, korupciju, vardarbību ģimenē un ar ceļu satiksmes negadījumiem. Globalizācija, apstrīdama demokrātijas izpratne, nestabilā pasaules ekonomika, nekontrolējamais pasaules iedzīvotāju pieaugums un terorisms, īpašas “patikas” izrādīšana noteiktām valdošajām varām – tas viss novirza uzmanību no patiesām sociāla rakstura problēmām un no tām izrietošām turpmāk iespējamām krimināla rakstura darbībām Igaunijā.

The most important environmental factors for the environment and habitat of plants include temperature. Agro-industrial production requires up-to-date information on the state of thermal resources and the response of plants to global warming within each region. The purpose of the research is to evaluate the state of thermal resources and the dynamics of crop yields in the Northern Steppe of Ukraine. Material for the research was the results of observations of the temperature regime of the AISW Dnipro (1961–1990 and 1991–2018) and data of winter wheat, spring barley, corn, sunflower in stationary experiments on control variants (DPDG “Dnipro”). Statistical data were used to evaluate the data by period: arithmetic mean (M); standard deviation (S); confidence interval (CL0.05) probability (P); repeatability (P × 100 %). Statistical processing was performed using applications in Excel 2003 and Statistica (version 6). Analysis of the thermal regime data showed that in 1991–2018, the average temperature for the year increased by 1.0 °C compared to the climatic norm (1961–1990), by 0.9 °C during the warm and cold periods. vegetation period of early cereals and late crops – by 0.8–1.0 °С. The average rate of increase in the average annual temperature in 1961–2018 was 0.31 ° C/10 years. Between 1991 and 2018, there were 15 cases with temperatures above 9.5 °C, with a recurrence rate of up to 53 %. The last decade (2009–2018) is characterized by a further increase in temperature during the year – by 1.5 ° C, the vegetation of early cere-als – by 1.6 °C, and late crops – by 2.0 °C. It is established that the warming is due to the temperature increase in the cold season – in January, February and March by 1.1,71.7 °C. Positive anomalies occur in July and August (+1.5 ° C). For estimating thermal resources, the important characteristics are the average temperature of the coldest and warmest months of the year. January 10-year average temperatures steadily increased from (-6.5) °C in 1961–1970, to (-4.0) °C in 2011–2018. Their annual variability decreased. The recurrence of high temperature (> -5 °C) in January increased from 34–35 % in 1961–1980 to 73 % in 2011–2018. The average values of July temperatures for 10 annual cycles have steadily increased from 20.8 to 23.0 °C since 1970. The recurrence of temperature> 23.0 °C for 1961–1970 was 2 cases and has increased 2.5 times in recent years. This increases the likelihood of sleepless periods. The positive trend leads to a shift in the dates of the steady transition of the average daily air temperature through 5 °C and the duration of the growing season. Over the last 18 years (2001–2018), it increased by 11–16 days (225 and 209–214). The incidence of such cases increased from 22 % to 44–50 %. At the same time, the increase in the duration of the period with an average daily temperature of ≥10 °C is not statistically significant. The average sums of effective temperatures ≥5 °C over the 10-year cycles in 2011–2018 were 2711 °C, which is 347 °C higher than the base period (1961–1990). Temperature totals increase linearly from 1971 to 2018. However, their recurrence (≥2711) in 2011–2018 sharply increases to 50 %. A close correlation (R2 = 0.75) was established between the duration of the period at ≥5 °C and the sum of effective heat ≥5 °C. A similar trend is typical for effective temperatures at ≥10 °C. The results of the accounting of crops show that for the whole period of observations their average values were: winter wheat (steam) – 4.44 t/ha; spring barley – 2.40 t/ha; corn – 4.32 t/ha; sunflower – 2.15 t/ha. Their distribution was characterized by significant fluctuations due to the variability of weather conditions. However, its maximum levels were noted in the post base period. Against the background of increasing supply of thermal resources in the region, there is an increase in their average yield: steam of winter – by 36 % (3.76 and 5.12 t/ha); spring barley – 24 % (2.14 and 2.65 t/ha ), corn – 11 % (4.14 and 4.59 t/ha), sunflower – 30 % (1.86 and 2.42 t/ha). The probability of forming the optimal yield level of steam winter, spring barley, corn and sunflower (≥4,44; ≥2,40; ≥4,32; ≥2,15 t/ha, respectively, for crops) in the post base period reaches 56–76 % whereas in 1961–1990 it was 25–43 %. Keywords: thermal resources, sum of temperatures, field crops, yield dynamics, adaptive properties.

Although the population registration in Indonesia has long been put through, the result is still unreliable, thus population census should be considered as a major source in providing data of population and households. Since its independent status, Indonesia has carried out the census for five times: in 1961, 1971, 1980, 1990, and in 2000 with the goals of providing a considerable amount of details of population data such as: buildings and households, villages potential (potensi desa or podes), and main pattern frames for survey and others census applications.The collected data contain information of households and individuals by the census taking system both de jure and de facto for the entire population of Indonesia, including those living abroads such as diplomatic corps with their family members. For the 2000 population census of Indonesia or SP 2000, the data of household and population by temporary residence status, have been put through by the national Central Bureau of Statistic, whereas the data of those by permanent residence status have been carried out by the Regional Central Bureau of Statistic, which are all predicted would be finished before the end of the year of 2000.

<strong><span style="font-family: TimesNewRomanPS-BoldMT;"><span style="font-family: TimesNewRomanPS-BoldMT;"><p align="left"> </p></span></span><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;">SAMMENDRAG</span></span></strong><span style="font-size: x-small; font-family: TimesNewRomanPSMT;"><span style="font-size: x-small; font-family: TimesNewRomanPSMT;"><p align="left">Hypoteser basert på funn fra tidligere studier av misdannelser hos barn av fedre i ulike yrkesgrupper (1), ble</p><p align="left">etterprøvet i et norsk registermateriale. Materialet besto av data fra Medisinsk fødselsregister (MFR) 1970-93,</p><p align="left">koblet med data fra Folke- og boligtellinger (FOB) fra 1970, 1980 og 1990 med opplysninger om bl.a. fars</p><p align="left">yrke. Som referansepopulasjon ble benyttet barn av fedre med alle andre yrker enn det som ble analysert.</p><p align="left">Barn av malere hadde tendens til økt risiko for spina bifida – OR 2,03 (CI 0,99–3,75) og barn av trykkeriarbeidere</p><p align="left">hadde økt risiko for klumpfot – OR 1,52 (CI 1,10–2,10). Studien har bidradd til å sannsynliggjøre</p><p align="left">en kausal sammenheng knyttet til påviste samvariasjoner, dog uten å belyse mekanismer. Tidligere positive</p><p align="left">funn hos barn av fedre i enkelte store yrkesgrupper som lærere, elektriske yrker, salgsrelaterte yrker, bønder</p><p align="left">og sjåfører ble ikke bekreftet i vårt materiale. Eventuelt falske negative funn kan skyldes lav statistisk styrke</p><p align="left">på grunn av små grupper eller problemer med ikke differensiell feilklassifisering av eksposisjon.</p><span style="font-size: x-small; font-family: TimesNewRomanPSMT;"><span style="font-size: x-small; font-family: TimesNewRomanPSMT;"><p align="left">Irgens Å, Krüger K, Skorve AH, Irgens LM.</p></span></span></span><span style="font-size: x-small; font-family: TimesNewRomanPSMT;"><p align="left"> </p></span></span><p align="left"><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;">Birth defects and paternal occupational exposure.<p align="left">Hypotheses derived from previous studies tested in a Norwegian registry material.</p></span></span></strong><em><span style="font-size: x-small; font-family: TimesNewRomanPS-ItalicMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-ItalicMT;"><em><span style="font-size: x-small; font-family: TimesNewRomanPS-ItalicMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-ItalicMT;"><p align="left">Nor J Epidemiol</p></span></span></em></span><em><span style="font-size: x-small; font-family: TimesNewRomanPS-ItalicMT;"><p align="left"> </p><p align="left"><p align="left">Aim</p></p><p align="left"> </p><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><p align="left">Method</p></span></span></strong></span><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><p align="left"> </p></span></strong></span><p align="left"> </p><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><p align="left">Results</p></span></span></strong></span><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><p align="left"> </p></span></strong></span><p align="left"> </p><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><p align="left">Conclusion</p></span></span></strong></span><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><p align="left"> </p></span></strong></span><p align="left"> </p></strong><span style="font-size: x-small; font-family: TimesNewRomanPSMT;"><span style="font-size: x-small; font-family: TimesNewRomanPSMT;">. The study gave evidence of cause effect relationships in the confirmed positive associations,<p align="left">though without any clarification of possible mechanisms involved. Possible false negative findings might be</p><p align="left">due to low statistical power as a result of small occupational groups or non differential problems of misclassification</p><p>of exposure.</p></span></span></strong><span style="font-size: x-small; font-family: TimesNewRomanPSMT;"><span style="font-size: x-small; font-family: TimesNewRomanPSMT;">. Offspring of painters had a tendency of increased risk of spina bifida – OR 2,03 (CI 0,99–3,75) and<p align="left">offspring of printers had an increased risk for talipes – OR 1,52 (CI 1,10–2,10). Positive associations</p><p align="left">observed previously in offspring of fathers in large occupational groups such as teachers, drivers, electricity</p><p align="left">related occupations, sales related occupations and agricultural workers were not confirmed in this dataset.</p></span></span></strong><span style="font-size: x-small; font-family: TimesNewRomanPSMT;"><span style="font-size: x-small; font-family: TimesNewRomanPSMT;">. The study was based on all births in Norway 1970–1993 for which linkage with population censuses<p align="left">1970, 1980 and 1990 could be obtained – about 1 million births. The reference population was offspring of</p><p align="left">the group that did not belong to the actual occupation.</p></span></span></span></em></span><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;">ENGLISH SUMMARY<strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"></span></span></strong></span><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><p align="left"> </p></span></strong></span></strong><span style="font-size: x-small; font-family: TimesNewRomanPSMT;"><span style="font-size: x-small; font-family: TimesNewRomanPSMT;">. To test, on the basis of a Norwegian registry material, previously established hypotheses on associations<p align="left">of birth defects with paternal occupation (1).</p></span></span></em><span style="font-size: x-small; font-family: TimesNewRomanPSMT;"><span style="font-size: x-small; font-family: TimesNewRomanPSMT;">1997; </span></span><strong><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;"><span style="font-size: x-small; font-family: TimesNewRomanPS-BoldMT;">7 </span></span></strong><span style="font-size: x-small; font-family: TimesNewRomanPSMT;"><span style="font-size: x-small; font-family: TimesNewRomanPSMT;">(1): 13-18.</span></span></p>

This paper aims to investigate major determinants of interprovincial migration in Turkey until 2010. In recent decades the magnitude of migration in absolute terms has increased considerably: During 1975-1980, 3.6 million people migrated, which constitutes 9.4% of the total population. These numbers have increased to 6.7 million people and 11.2% in the 1995-2000 period. The rate of increase is especially tremendous for the 1985-1990 period with 41%. Over the years the composition of migration has also changed: In the past rural-to-urban migration was predominant; however, today there is remarkable amount of urban-to-urban migration. During 1975-1980, 66% of the total migrants were towards urban centers, which increased to 75% during 1995-2000. On the other hand, the percentage of total migrants towards the village centers declined from 34 to 25 in the respective periods.
 From 2008 on, the Turkish Statistical Institute (TUIK) started publishing yearly unemployment statistics at provincial level, which permits an analysis of Turkey’s migration patterns within the Harris-Todaro framework. Moreover since 2007, TUIK started implementing Address Based Population Registration System, which enables tracking migration moves continuously, rather than by intermittent five to ten year periods. However, data was not adequate to test Turkey’s migration within the Harris-Todaro framework, especially due to lack of average wages at the provincial level. Therefore, utilizing the 2010 provincial level data, we tried to explain Turkey’s internal migration based on variables such as population born outside of their current province, number of university students, and a proxy variable we developed for average wages.