Because the value of the **Pearson** **correlation** **coefficient** is of 0.43 for a significance level of 0.05, it results that hypothesis 2e holds true, allowing us to conclude that there is a statistically significant positive **correlation** between the extent to which the producers in the bakery industry use direct marketing as a means of communication and the situation of the orders and the calculation of their monetary value as an evaluation tool for its efficacy. At the same time, one can notice that there is a statistically significant positive **correlation** between the extent to which the companies in the bakery sector use direct marketing and the analysis of the client databases as a measurement tool of the efficacy of this way of communication (the value of the **Pearson** **correlation** **coefficient** being 0.56 for a significance level of 0.01). At the same time, the value of the **Pearson** **coefficient** of 0.17 obviously shows that between the extent to which the producers in the bakery industry use as a means of communication direct marketing and the situation of the number of answers correlated to the number of direct mails sent as an evaluation tool for its efficacy there is no significant **correlation** statistically.

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Data were analyzed by SPSS statistical software version 20.0 using **Pearson** **correlation** **coefficient** for **correlation** between health belief model structures (perceived susceptibility, perceived severity, perceived benefits, perceived barriers, perceived self- efficacy), with nutritional preventive behaviors of osteoporosis, and ANOVA for relationship between parents' educational level, parent`s job and family income level with nutritional preventive behavior of osteoporosis at the significant level 0.05. 3- RESULTS

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The Pearson correlation coefficient was used to reveal correlations between field ages, plant traits for both species and community levels, community structural attribute[r]

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Table 5. **Pearson** **correlation** **coefficient** between the assessed characteristics: plants lodging (PL), plant height (HEI), injury related to all treatments (INJ), number of plants per square meter (NPM), number of pods per plant ( NPP), number of grains per pod (GP), mass of 400 grains (HG, g), harvest index (HI) and grain yield (YIELD) in the treatments with inhibitors of auxin. UTFPR, Campus Pato Branco

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Shift patterns of plant trait- species abundance relationships along a range of environmental properties. To test whether any potential plant trait-species abundance relationships were affected by the seven environmental properties, the 31 **Pearson** **correlation** **coefficient** r values that were generated at the plot scale for each trait in the trait-species abundance relationship were correlated separately with each of air humidity, soil moisture content, soil temperature, soil pH, and soil organic matter, N and P contents. A significant relationship between an environmental property and the r-value of a trait- abundance relationship showed that the strength of the **correlation** between plant trait and species abundance was shifting across the range of environmental property. This is a result that describes every significant relationship between the r-value of a trait- abundance relationship and an environmental property. On this basis, a significant direction shift of a trait-abundance relationship across a range of environmental measurement emerged only when the direction of a trait-abundance relationship reversed across an environmental property. The reversed direction was defined here as the change of **correlation** coefficients of the trait-abundance relationship from positive to negative (or vice/versa) across the range of values of the environmental property [19]. If the **correlation** coefficients remain positive or negative in the whole range of the environmental property, this means that there was no significant direction reversal in a plant trait-species abundance relationship.

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ment, the computerized ergospirometric system w as used (VO- 2000, Aerosport, M edgraphics, St. Paul, M innesota) and for the indirect V O 2max measurement, the 3,200 m field test w as performed. The statistical analysis w as elaborated through the t-Student test for paired samples and through the **Pearson** **correlation** **coefficient**. The V O 2max values obtained in the direct measurement test pre- sented no significant differences in relation to the indirect mea- surement (62.8 ± 10.1 vs. 58.5 ± 8.5 ml/kg/min, respectively). When the V O 2max values obtained in both tests w ere correlated, a strong **correlation** (r = 0.72) w as observed. In short, the indirect measure- ment tests presented good acceptance among indoor soccer play- ers due to the high **correlation** w ith the direct measurement tests, the low cost and the attainment of important information that w ill be helpful in the training prescription and follow -up.

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The analysis included only parasite species with prevalence higher than 10% (BUSH et al., 1990). The Spearman rank **correlation** **coefficient** (rs) was calculated to determine possible correlations between host length and total abundance of parasites. The **Pearson** **correlation** **coefficient** r was used as an indication of the relationship between the total length of the host and parasite prevalence, with further prior processing of prevalence data (ZAR, 1996). The Student t test was used to make comparisons with data from Paraguassú et al. (2002), in order to ascertain whether the relationships remained the same after 12 years. This test was used for statistical comparisons between the quantitative characteristics of the metazoan infracommunities, using data from Paraguassú et al. (2002). The species diversity of the parasite was calculated using the Brillouin index (H), given that each fish analyzed corresponded to a full sample community (ZAR, 1996), so as to ascertain whether the diversity values remained similar after 12 years. The likely variation in sex-related host diversity was analyzed using the Mann-Whitney U test, and the host total length was tested using the Spearman **correlation** **coefficient**, and the results were compared with the study of Paraguassú et al. (2002). The possible interspecific association between the competing species

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slight tendency of low descriptor values are related to a high percentage of green areas. However, due to the multitude of variables influencing the subareas, this relationship was not so clear. Therefore, the cluster analysis has become more useful, clarifying this relationship. When the subareas were divided into groups, there was often an increase in the **correlation** between subareas and noise descriptors. Consequently, the results show that the **correlation** **coefficient** between green areas and noise pollution may vary according to the characteristics of the subareas. The cluster presenting the most attenuating effect of the green areas was class 3, where there are a greater number of health facilities and educational buildings. This effect may be related to the particular concentration of activities occurring in this area, which increases road traffic and the number of sound sources (KINDA; LE COURTOIS; STÉPHAN, 2017; SAKIEHet al., 2017).

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Clinical statistical data were analyzed by the IBM SPSS Statistics 22.0. The kappa value was used to assess intra- and inter-observer agreement, with kX0.7 indicating excellent agreement, 0.754kX0.4 indicating passable agreement, and ko0.4 indicating poor agreement. The Spearman **correlation** **coefficient** between the severity of intervertebral disc injury and the AO fracture type was calculated. A chi- square (w 2 ) test was adopted to measure the variability

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The level of synchronization among the countries integrated in the European Monetary Union (EMU) is one of the most important criteria for an optimal economy. As such it is of great importance to study how these countries are related to each other. Using a dynamic factor model Kose et al. (2008) found evidence of an increase in convergence among industrial economies during the globalization period. These findings are aligned with the ones provided by Ferroni and Klaus (2015) which suggest a high level of interdependence between Germany, France and Italy while Spain seems more dependent on domestic factors. Using a cross **correlation** analysis similar to the one used in this project, Álvarez et al. (2010) also concluded that, when using GDP as a variable of comparison, there is a high level of **correlation** between those same economies. Moreover Mink et al. (2008) using synchronicity and co-movement measures found a high **correlation** between business cycles in France, the Netherlands, Spain and Germany while Ireland and Greece show a lower **correlation** with the remaining EMU countries.

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The Pearson Product-Moment Correlation analysis showed a significant negative relationship between depression and neuropsychological composite variables (executive function, lea[r]

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The results show that the air content in the mortars mixture increases with the fiber content, independently of the type of mortar. This probably happens because the addition of fibers changes the mortar rheology and prevents the air from escaping. A recent study using 0.2% of 6 mm PVA fiber shows that fiber addition can significantly increases the required mixing energy to achieve more homogeneous mortars (FRANÇA; CARDOSO; PILEGGI, 2016). This is less significant in MC mortar, which has already higher air content, presenting a maximum of 20% increase in air content when fibers are added. ML mortars shown an increase of 300% in air content when 0.3% of fibers are added, although the air content in ML mortars is low if compared to MC. Also, the **correlation** between air content and fiber addition, plotted in Figure 4, present similar a pattern for both mortars.

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In this way, a script with functions of the statistical program R was developed to calculate and to identify the cophenetic **correlation** **coefficient** of the cluster analysis hierarchical method more accurate for a data set. This guide purpose is to facilitate the study of researchers who are not from the statistical area or are not familiar with the program.

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Menezes et al. (2010) conducted a study of the **correlation** between the pollen types Mimosa pudica and Eucalyptus, which are the most frequent types in the apicultural pollen from the municipality of Alagoinhas (Bahia), and the levels of phenolic compounds of the same samples. In their analyses of the samples with the highest occurrence of Mimosa pudica, the average levels of phenolic compounds was 33.34±0.46 mg GAE/g, and in the samples with the highest occurrence of Eucalyptus the average levels of phenolic compounds was 67.83±0.93 mg GAE/g. Through the Spearman **correlation** **coefficient** they identified a negative **correlation** between levels of total phenolic compounds with the pollen type Mimosa pudica (Rs=-0.5066) and a positive **correlation** with the type Eucalyptus (Rs=0.6666), whereas in our study of samples from the territory of the Agreste of Alagoinhas the **correlation** was negative for both types. There was however a positive **correlation** with the types identified as Asteraceae I, Borreria verticillata, Mikania and Mitracarpus longicalyx. Further studies including a larger number of samples are needed to establish whether the association of the **correlation** of the levels of total phenolic compounds with these pollen types is indeed valid for propolis produced in this region.

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mode. The intraobserver ICC values for peripapillary RNFL thickness measurements on HS mode with the EBF function activated were ≥ 0.98 in all but TS (0.97) and T (0.93) regions. Serbecic et al. compared the detection of RNFL measurements using either HS or HR image-acquisition mode and found highest **coefficient** of variation in the temporal sector with no significant differences between the mode of image acquisition. 29 The high reproducibility of peripapillary RNFL thickness measurements with the Spectralis can be attributable to different technical factors such as improved image resolution, imaging speed (40,000 A-scans/second) or retinal segmentation algorithms. However, given the results of the current study, it is likely that its improved reproducibility has also been positively influenced by the EBF function. Moreover, the overall greater ICC values obtained for HS scanning may be related, at least in part, to the fact that the ART tool wasn’t utilized during HR scanning.

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Abstract This paper aims to establish the **correlation** between statistical parameters and Electroencephalographic (EEG) signals as a function of age, in subjects without neurological disorders. EEG signals were recorded during the task of following an Archimedes spiral. There were 59 healthy subjects who voluntarily participated in this study which were divided into 7 groups, aging between 20 to 86 years from both gender, in order to identify differences and allow discrimination between the features of each group. Initially, comparisons were made among several features (F20, F50, F80, F95, Mean Frequency, Root Mean Square value, Zero Crossings, Square of the Power Spectrum, Kurtosis, Skewness, Variance, Standard Deviation and Approximate Entropy) seeking separation between young and elderly groups. Furthermore, it was sought to correlate the statistical parameters and the entire age range. For this purpose it was used Linear Discriminant Analysis (LDA). The data were processed with MATLAB ® software. Through the LDA, signiicant differences were observed

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Results indicated that many yield contributing traits viz; plant height, leaf length, leaf width, NOL, in- vitro dry matter digestibility and dry matter yield had positive and significant **correlation** at genotypic as well as phenotypic level with green fodder yield (Table 2) and the selection based on these traits will result in improving the green fodder yield in maize. Kara et al. (1999) reported that the green forage yield in maize was positively correlated with stem diameter, ear diameter, and ear weight. On the contrary, number of cobs/plant, number of seeds/cob and acid detergent fibre exhibited a negative and significant **correlation** with green fodder yield and dry matter yield as well, whereas rest of the traits under study did not

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Today, the development of tourism in all national, regional and international aspects is under the attention of the government, policy makers and private sector activities. This approach had an important role in developing road transport and increasing travels. Thus, roads are considered as the main infrastructure that can result in local tourism development. Field exploration of Kermanshah- Hamedan axis was the aim of this procedure. Transportation maps and random interviews with tourists were done by using Cochran formula descriptive statistics was used for data arrangement. Spearman and **Pearson** **correlation** test were used to evaluate the variables. The results indicated a significant **correlation** between expansions of roads and the growth of tourism which led to an increase in the number of road accidents.

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As the **correlation** structure for the fragment remains constant, it could be verified that the sampling size (n) will determine how the addition of the **correlation** **coefficient** will impact the estimator of the variance of the mean, i.e., the greater the sampling rate, the larger the impact of this factor on the inventory error. Table 3 clearly emphasizes this point by demonstrating that as the sampling rate decreases, the impact of **correlation** on the inventory accuracy decreases [difference in the error estimations between SRS and Cochran (1965)]; however, this still had a good advantage over the use of the classical estimator for the evaluated fragment. It was verified that there was a reduction in the percentage error between the SRS and the Cochran estimator, ranging from 14% to 28% approximately. It was observed that even when 50% of the area was sampled with the SRS estimator, there was no error lower than 10%. Using the **correlation** **coefficient** for samples 1 and 2, the error was approximately 10%.

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The differences in the inversion frequencies between collections were highly significant (χ 2 = 7 4.2, d.f. = 32, p < 0.001). The frequency of DA varied periodically (Fig- ure 2), as it increased in cool months (end of fall and winter) and decreased in hot months (end of spring and summer), but we were unable to fit this to a sinusoidal curve. None- theless we could find a quadratic function with very good fit (y = -0.0351 x 2 + 0.1781 x + 0.6037; r 2 = 0.89; p < 0.01). There was a significant negative **correlation** with tempera- ture (r = -0.90, p < 0.001, for the average temperature) and precipitation (r = -0.75, p < 0.05) (Table 2). The inversion DS showed an opposite pattern, since its frequencies in- creased in the hot months and fell in the cool months. The inversions DI (Figure 3) and DP did not vary cyclically, al- though, when DP was pooled with DS, a very clear pattern was observed (Figure 4), and a quadratic function could be successfully adjusted (y = 0.0348 x 2 -0.1643 x + 0.6184; r 2 = 0.62; p < 0.01). The **correlation** coefficients for the inver- sion frequencies versus altitude and climatic variables are shown in Table 2. Figure 5 shows the distribution of DA, DI and DS+DP inversion frequencies in relation to the average temperature.

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