ABSTRACT ROBUSTNESS OF TWO FORMULAS TO CORRECT PEARSON CORRELATION FOR RESTRICTION OF RANGE by Dung Minh Tran Many research studies involving Pearson correlations are conducted in settings where one of the two variables has a restricted range in the sample. For example, this situation occurs when tests are used for selecting candidates for employment or university admission. Often after selection, there is interest in correlating the selection variable, which has a restricted range, to a criterion variable. The focus of this research was to compare Alexander, Alliger, and Hanges’s (1984) formula to Thorndike’s (1947) formula and population values using Monte Carlo simulation when the assumption of normal distribution is violated in a particular way. In both Thorndike’s and Alexander et al.’s correction formulas, values for the variances in the restricted and the unrestricted situations are required. For both formulas, the variance in restricted situations was a sample estimate. In the Monte Carlo simulation, the difference between the two approaches was that in Thorndike’s formula, the variance in the unrestricted situation was the population variance from the exogenous variable, whereas in Alexander et al.’s approach, the population variance was estimated based on the sample variance in the restricted situation. In the simulation, robustness situations were created from non-normal distributions for predicted group membership in a classification problem. As expected, Thorndike’s corrected correlation values were more accurate than Alexander et al.’s corrected correlation values, and Thorndike’s formula had a smaller standard error of estimates. Absolute values of the mean differences between the estimated and population correlations for Alexander et al.’s approach compared to Thorndike’s approach in robustness situations ranged from 1.37 to 2.15 larger. Nevertheless, Alexander et al.’s approach, which is based only on estimated variances, appears to be a worthwhile correction in most of the simulated situations with a few notable exceptions for non-normal distributions.

The purpose of this study was to survey the levels of job satisfaction among full-time faculty members at a selected Mississippi community college using the constructs of Herzberg’s Motivation-Hygiene Theory as defined by Wood (1973). The researcher used Wood’s 1976 refined Faculty Job Satisfaction/Dissatisfaction Scale to discover the participants’ levels of total job satisfaction; to discover the participants’ levels of overall job satisfaction; to compare the means of total job satisfaction factors to the mean of total job satisfaction; and to examine the correlation of the faculty’s mean responses to the total job satisfaction individual questions to the mean of the overall job satisfaction. The target population of this study was all full-time faculty at a Mississippi community college. The population consisted of 152 full-time faculty members. The findings of the survey indicated that the 85 participants were moderately satisfied with their jobs. The survey was designed to incorporate 2 treatments to ask the respondents to answer questions about job satisfaction. The participants chose a higher value on the Likert scale when asked the single question relating to overall job satisfaction. When the information was broken down into factors, the participants rated their job satisfaction lower. The Wilcoxon results stated the 2 treatments were significant at alpha level .05, and the null hypothesis was rejected, meaning there was a difference in the responses with two treatments of surveying respondents.

To characterize the size distributions, concentrations and sources of heavy metal associated with suspended particles, a total of 12 months of sampling periods were taken by Micro-Orifice Uniform Deposit Impactor (MOUDI) in the Nantzu Export Processing Zone from January to December 2011, The concentrations of suspended particles ranged from 54.7 to 203 £gg/m3. Both autumn and winter had significantly higher levels of suspended particles than in spring and summer. The mass concentrations of fine particles accounted for ~50% of the mass concentrations of suspended particles. The mass concentrations of PM2.5 accounted for 50.2-70% of the mass concentrations of PM10. The mass concentrations of PM1 accounted for 24-38.3% of the mass concentrations of PM10. These results indicated that fine particles dominated in atmospheric particulates in Nanzih Export Processing Zone. In addition, among the PM10, PM2.5 and PM1, significant correlations were found. The crustal elements (Al, Fe, Ca, Mg, K and Na) and sulfate are dominant during the sampling periods, which accounting for ~95% of the total concentrations. The crustal elements were observed mainly in coarse particles, while sulfate was found mainly in fine particles. The concentrations of all crustal elements decreased in summer could be attributed to the meteorological conditions and chemical mechanism. By using the enrichment factor (EF) to distinguish the sources of heavy metals in PM10, PM2.5 and the results showed that EF values of crustal elements in PM10 ranged from 1 to 10, suggesting PM10 might come from the resuspension of soil and road dust. In addition, Pb, Zn, As, Se, Mo, Sb and sulfate were observed at higher EF values in both PM2.5 and PM1, indicating the influence of anthropogenic emissions in fine particles. The results from Pearson¡¦s correlations indicated that PM10 in the Nantzu Processing Zone were mainly from the resuspension of soil and road dust, while fine particles (PM2.5 and PM1) may be from the traffic emissions and petrochemical industry in Nanzih and Renwu.

The topic of National Innovation System (NIS) is gradually emphasized. The NIS includes four compositions. They are government, industry, university and public research organization. The knowledge flow is transmitted among the four compositions through innovation policy. Thus, many countries have begun to develop NIS. The NIS will raise the economic growth rate, and promote the competitiveness of industry. Consequently, the study of NIS becomes very popular. OECD (Organization for Economic Cooperation and Development) build particular NIS structures to explain the difference between members, and try to find the key successful way to achieve national innovative goals. In the Asia, the Taiwan, China, Japan and South Korea show high relationship in the politics and economics. Japan and South are high-developing countries, and their innovation activities are very successful in the world, especially in those of technology industry. Additionally, China has abundant natural resources to help them develop technology industries. For above reasons, we elect these countries to be studied, and we try to find the essential factors of successful NIS. This study includes two research issues. We first collect the secondary data to explain different NIS structure among four countries. Then, we use Stepwise Regression Analysis to evaluate the performance of innovation. Finally we use the Pearson Correlation Analysis to analyze relationship between NIS performance and semiconductor industry development. The results of this study include: (1) R&D expenditure is the most important factor to influence the performance of national innovation; (2) Expenditure on basic research is an important factor to influence the output of innovation; (3) national innovation and industry development shows high relationship; and (4) the ranking of national innovation performance is not totally the same as that of industry development. Based on these findings, we will provide some important policy suggestions for innovation activities in Taiwan.

With the shift toward online shopping, it has become necessary to customize customers' needs and give them more choices. Before making a purchase, buyers research the products' features. The recommender systems facilitate the search task for customers by narrowing down the search space within specific products that align with the customer's needs. A recommender system uses clustering to filter information, calculating the similarity between members of a cluster to determine the factors that will lead to more accurate predictions. We propose a new method for predicting scores in machine learning recommender systems using the Gaussian mixture model clustering and the Pearson correlation coefficient. The proposed method is applied to MovieLens data. The results are then compared to three commonly used methods: Pearson correlation coefficients, K-means, and fuzzy C-means algorithms. As a result of increasing the number of neighbors, our method shows a lower error than others. Additionally, the results depict that accuracy will increase as the number of users increases. Our model, for instance, is 5% more accurate than existing methods when the neighbor size is 30. Gaussian mixture clustering chooses similar users and takes into account the scores distance when choosing nearby users that are similar to the active user.

Recently, research has begun to pay more attention to the cognitive functions associated with auditory perception. In this study, two tests are performed to investigate the correlation between the ability to recognise speech-in-noise and the performance of sensory memory, as well as to investigate whether the performance would improve during the sensory memory test. For measuring speech-in-noise, the Hagerman test was used. A random noise test to detect deviant noises was used to measure sensory memory. In total 16 participantstook part in the study (mean age=24.8125, SD=3.14), half of the group began with the Hagerman test, and the other half with the random noise test. Two different statistical analyses were performed on the data. For examining the correlation between the performance on the Hagerman test and the random noise test, a Pearson correlation was used. The results were as follows: p = 0.4962, r = -0.1835734. Observing the results, the tests did indicate a slight negative correlation regarding the r-value, but not a significant correlation. Thus, the analysis did not derive any significant results. The second analysis was a dependent t-test to examine whether there was an improvement in performance during the random noise test, as it was divided into four separate blocks. The analysis showed the following results: t = 1.0266, df = 28.943, p = 0.3131. These results were not significant, though observing the block graph might indicate a tendency for improvement. For further studies, the random noise test should perhaps be modified into an easier version. This is based upon the data, as many of the participants merely got a score above, or even below, chance. Further studiesshould also use a higher number of participants as well to increase the chance of receiving significant results from the tests.

No description available.

In the fall of 2006, soils from three small valleys in the Laxemar/Oskarshamn area were sampled. A total of eight composite samples were characterized for a number of soil parameters that are important for geochemical sorption and were later also used in batch sorption experiments. Solid/liquid partition coefficients (Kd values) were then determined for seven radionuclides in each of the eight samples. To contribute to the interpretation of the sorption results together with the soil characterizations, this study aims to describe the sorption behavior of the radionuclides caesium, nickel and uranium and also discern which parameters that could provide a basis for estimating the strength of sorption of radionuclides in general. The methodology included quantitative methodologies such as compilation of chemical equilibrium diagrams by the software Hydra/Medusa and correlation analyses using the statistical software SPSS statistics. Based on the speciation diagrams of each radionuclide and identified important linear and non-linear relationships of the Kd values with a number of soil parameters, the following soil- and soil solution properties were found to have controlled the sorption of Cs, Ni and U, respectively, in the Laxemar soils. Cs: the specific surface area of the soil coupled to the clay content. Ni: the cation exchange capacity, alkaline solution pH, soil organic matter and dissolved organic matter. U: the cation exchange capacity, soil organic matter, dissolved organic matter, dissolved carbonate and alkaline solution pH. The soil that showed the strongest sorption varied between the nuclides, which can be related to the individual sorption behavior of caesium, nickel and uranium, as well as the different physicochemical properties of the soils. The parameters that should be prioritized in characterizations of soil samples are identified to be: solution pH, the cation exchange capacity, the specific surface area of the soil, soil organic matter and soil texture (clay content). / För att kunna fatta beslut relaterade till hypotetisk framtida kontaminering från slutförvar av radioaktivt avfall är det direkt avgörande att förstå mobiliteten av radioaktiva element i miljön. Sorption är en av de viktigaste kemiska mekanismerna som kan minska spridningen av radionuklider i vatten/jord/bergssystem, där nukliderna fördelar sig mellan vätskefasen och ytor på fasta partiklar i dessa system. Fördelningskoefficienter (Kd värden) används generellt som ett kvantitativt mått på sorptionen, där ett högt Kd värde innebär att en större andel av ämnet i fråga är bundet till den fasta fasen. Under hösten 2006 togs jordprover från tre dalgångar i Laxemar/Oskarshamn. Totalt åtta jordprover karakteriserades för ett antal jordparametrar som är viktiga för geokemisk sorption och användes senare i batchförsök tillsammans med ett naturligt grundvatten. Fördelningskoefficienter (Kd värden) bestämdes för sju radionuklider (Cs, Eu, I, Ni, Np, Sr and U) för vart och ett av de åtta jordproverna. För att bidra till tolkningen av sorptionsresultaten tillsammans med jordprovernas egenskaper syftar denna studie till att beskriva sorptionsbeteendet hos radionukliderna caesium, nickel och uran samt urskilja vilka parametrar som kan fungera som grund för att uppskatta sorptionsstyrkan av radionuklider i allmänhet. För att uppnå detta syfte så har studien följande mål. Identifiera de jord- och marklösningsegenskaper som kontrollerar sorptionen av Cs, Ni respektive U i de åtta Laxemar proverna. Bestämma vilket Laxemar-jordprov som starkast sorberar de tre radionukliderna. Identifiera de jordparametrar som bör prioriteras vid jordkarakteriseringar, baserat på deras sorptionsinflytande, för att kunna uppskatta Kd värden endast med begränsad information om ett jordsystem. Metoden innefattade kvantitativa metoder såsom sammanställning av kemiska jämviktsdiagram med programvaran Hydra/Medusa och korrelationsanalyser med hjälp av statistikprogramvaran SPSS statistics. De kemiska jämviktsdiagrammen bidrog till att beskriva specieringen av respektive nuklid som en funktion av pH och korrelationsanalyserna bidrog till att identifiera linjära samband mellan par av variabler, tex mellan Kd och jordparametrar. Baserat på specieringsdiagrammen för varje radionuklid och identifierade viktiga linjära och icke-linjära förhållanden mellan Kd-värdena och ett antal jordparametrar har följande egenskaper hos jordarna och marklösningen visat sig huvudsakligen kontrollera sorptionen av Cs, Ni respektive U i de åtta Laxemar jordarna: För caesium gäller jordens specifika ytarea kopplad till lerinnehållet, medan för nickel är det katjonbytarkapaciteten, organiskt material, alkaliska pH-värden samt löst organiskt material. Sorptionen av uran befanns kontrolleras av katjonbytarkapaciteten, organiskt material, löst organiskt material, alkaliska pH-värden samt lösta karbonater. Den jord som visade starkast sorption varierar mellan de tre nukliderna, vilket kan relateras till nuklidernas individuella sorptionsbeteende i jord samt jordarnas olika fysikaliska och kemiska egenskaper. Parametrarna som bör prioriteras vid karaktärisering av jordprov identifierades vara: pH, katjonbytarkapaciteten, jordens specifika ytarea, mängden organiskt material samt jordtexturen (lerinnehåll).

In this thesis, an analysis of Bitcoin, Monero price and volatility is conducted with respect to S&P500 and the VIX index. Moreover using Python, we computed correlation coefficients of nine cryptocurrencies with two different approaches: Pearson and Spearman from July 2016 -July 2018. Moreover the Pearson correlation coefficient was computed for each year from July2016 - July 2017 - July 2018. It has been concluded that in 2016 the correlation between the selected cryptocurrencies was very weak - almost none, but in 2017 the correlation increased and became moderate positive. In 2018, almost all of the cryptocurrencies were highly correlated. For example, from January until July of 2018, the Bitcoin - Monero correlation was 0.86 and Bitcoin - Ethereum was 0.82.

Nos últimos anos, o estudo de propriedades de redes espaciais urbanas conhecidas como centralidades, tem sido utilizado com frequência para descrever fenômenos de ordem sócio-econômica associados à forma da cidade. Autores têm sugerido que centralidades são capazes de descrever a estrutura espacial urbana (KRAFTA, 1994; ANAS et al., 1998) e, portanto através do estudo de centralidades, é possível reconhecer os espaços que mais concentram fluxos, os que possuem os maiores valores de renda da terra, os mais seguros, entre outros aspectos que parecem estar diretamente relacionados com o fenômeno urbano. A hipótese dessa pesquisa admite que centralidades em redes espaciais urbanas desempenham um papel fundamental na formação da estrutura espacial urbana e na maneira como são organizados os usos do solo da cidade. Assim, essa pesquisa investiga qual modelo de centralidade, processado sobre diversas formas de se descrever o espaço urbano na forma de uma rede, é capaz de apresentar resultados mais fortemente correlacionados com a distribuição espacial de atividades econômicas urbanas. Nessa pesquisa são avaliados cinco modelos de centralidade, aplicados sobre diferentes redes espaciais urbanas com a intenção de se verificar qual deles apresenta maior correlação com a ocorrência de atividades econômicas. Para realizar tal exercício, esses modelos são aplicados sobre três tipos de redes espaciais urbanas (axial, nodal e trechos de rua) – oriundas da configuração espacial de três cidades brasileiras – processados de forma geométrica e topológica. Os modelos de centralidade aplicados são conhecidos como centralidade por Alcance (SEVTSUK; 2010), centralidade por Excentricidade (PORTA et al.; 2009, 2011), centralidade por Intermediação (FREEMAN, 1977), centralidade por Intermediação Planar (KRAFTA, 1994) e centralidade por Proximidade (INGRAM, 1971). O coeficiente de correlação Pearson (r) é utilizado como ferramenta capaz de descrever qual modelo de centralidade, associado a qual tipo de representação espacial e qual modo de processamento de distâncias melhor se correlaciona com a distribuição de atividades econômicas urbanas nessas cidades. As evidências encontradas nessa pesquisa sugerem que os modelos de centralidade por Alcance, centralidade por Excentricidade e centralidade por Intermediação Planar destacam-se em comparação com os demais modelos processados. Além disso, os valores de correlação Pearson (r) mais relevantes foram obtidos quando os modelos de centralidade foram processados considerando-se a geometria da rede formada por trechos de rua, indicando que um tipo de representação espacial mais desagregada e processada de forma geométrica seria mais capaz de apresentar os melhores valores de correlação para a compreensão do fenômeno urbano estudado. / In recent years, the study of urban spatial networks has been often used to describe urban phenomena associated with the shape of the city. Researches suggested that centralities are able to describe the urban spatial structure (KRAFTA, 1994; ANAS et al., 1998) and then it is possible to recognize the spaces with more flows, which have the highest values of land revenue, the safest, among other aspects related to urban phenomenon. The hypothesis of this research accepts that centrality in urban spatial networks play a key role for the urban spatial structure and the way of land uses is organized. Thus, there would be some measures of centrality in urban spatial networks that would be more associated with economic activities occurring in the city. The research will evaluate five measures of centrality applied on three types of urban spatial networks (axial map, node map and segment map). Therefore we will use five models of centrality in urban spatial networks known as reach (SEVTSUK, MEKONNEN, 2012), straightness (PORTA et al., 2006b), betweenness (FREEMAN, 1977), planar betweenness (KRAFTA, 1994) and closeness (INGRAM, 1971) in order to determine which this most highly correlated with the occurrence of economic activities. The relationships between these measures of centrality and locations of economic activities are examined in three Brazilian cities, using as methodology the Pearson correlation coefficient (r). The highest correlation between the results of centrality in urban spatial networks and the location of economic activities will suggest which centrality measure, way of to describe urban space like a network and distance processing method (euclidian or topologic) is more associated with the occurrence of these activities in the city. The results indicate that Reach, Straightness and Planar Betweenness are most outstanding models of centrality. In addition, Pearson correlation coefficients (r) most relevant were obtained when models of centrality are processed considering euclidian paths in the street segments network, suggesting that this type of spatial network and distances processing method generates centralities with more significant correlation values within the urban phenomenon studied.