## Correlation Between Petrographic and Physico-Mechanical Variables of Basalts of the Parana Magmatic Province

Bruno Nagalli

Student, Geology Academic Department, The Federal University of Paraná,

Curitiba, Brazil. e-mail:

Eleonora Maria Gouvea. Vasconcellos

Professor, Geology Academic Department, The Federal University of Paraná,

Curitiba, Brazil.

André Nagalli

Professor, Civil Construction Academic Department, The Federal University of Technology – Paraná, Curitiba, Brazil.

Student, Geology Academic Department, The Federal University of Paraná,

Curitiba, Brazil. e-mail:

*brunonagalli@hotmail.com*Eleonora Maria Gouvea. Vasconcellos

Professor, Geology Academic Department, The Federal University of Paraná,

Curitiba, Brazil.

*e-mail: eleonora@ufpr.br*André Nagalli

Professor, Civil Construction Academic Department, The Federal University of Technology – Paraná, Curitiba, Brazil.

*e-mail: nagalli@utfpr.edu.br***Database Analysis**

Initially deciphering the results the study was conducted of the information in order to know the distribution and sampled amplitude. Samples of physical and mechanical tests were ranked in order of skyrocketing worth and diagrammatically compared to the amount of samples. In the graphical analysis it had been observed that though the distribution of the samples among the overall vary, where abrasion Los Angeles, durability and water absorption corresponding sample values occur while not gaps. In the case of the overall amplitude density distribution of the samples graphically is little because of the lithological monotony. Yet it will be understood that the information has near ideal state of affairs sampling distribution of physical-mechanical results, enabling employment in applied math correlation for this job.Petrographically the database has characteristics of mineral share and intrinsic grain size to lithotype delineated as volcanic rock by autoimmune disease MAITRE (1989).

**Results Interpretation**

In the early stages of labor were evaluated all the variables in line with the concepts of correlational statistics whose results indicate for the geologic risk of correlation and so the continuation of the analysis. The results obtained using the linear correlation coefficients of Pearson showed moderate positive correlation (higher than zero.3) between the grain size of the matrix (0.5430) and phenocrysts (0.4336) and the wear results by abrasion la. Mineral percentages in the linear correlation calculations of Pearson were significant for volcanic glass cloritizated with positive coefficients of zero.6083 proving the strong correlation ((higher than zero.6) between variables. The celadonite showed moderate association with negative correlation coefficient of zero.3155

In the analysis of scatter diagrams for the la Abrasion variable confirmed the trend of correlation between variables. There is the distribution of the samples in an exceedingly non aligned because the ideal pattern of correlation, however, is composing a distribution trend orientation, where the set of samples expresses the main orientation.

Interpreting the Scatter Diagrams conjointly found that the distribution of samples for volcanic glass cloritizated and the celadonite couldn't be linearly. To prove the non-linearity we used the calculation of Spearman's correlation. The results of the correlation coefficients were greater than the Pearson technique. Therefore calculations and scatter plots show that there is sturdy nonlinear degree of correlation to the volcanic glass cloritizated (0.7145) and moderate for samples containing celadonite (-0342).

The other variables of mineral proportion numerically categorical coefficient of correlation of but zero.3 being thus weak linear correlation. The same may be said for the calculations by Spearman technique. However the observation of Scatter Diagrams the incidence of iron hydroxide noteworthy. The linear correlation coefficient of Pearson calculated exposes associate quantity of -0.1147 weak correlation, but the interpretation of dispersion diagram reveals a trend of moderate non-linear negative correlation.

The obtained results meet the initial expectations of geological lines of reasoning with the tendency that the larger the amendment quantity of minerals and secondary higher can be the la Abrasion rates. Also interpret that the larger the particle size is larger mineral abrasive wear.

Linear Pearson Correlation method for sturdiness exhibited the same behavior of the la Abrasion. The degree of correlation between particle size of phenocrysts and the matrix obtained moderate coefficient of correlation being 0.4496 and 0.6322 respectively. The correlations between mineral percentages and durability tests reveal that the mineral has moderate positive linear correlation of zero.3532 and minerals quartz and obsidian cloritizated ar powerfully related to. The obsidian cloritizated showed a positive correlation constant of zero.7862, however, due to low number of sample pairs opted for the calculation by Spearman's technique, but the result was less communicative zero.6004. In the analysis of the scattergram interprets the linearity trend within the distribution of samples that ends up in conclusion positive linear correlation between variables.

The quartz in linear determination by the method of Pearson features a indirect correlation constant of -0.8958. Due to the quantity of samples with occurrence of quartz be but thirty (= 4), and the analysis of the dispersion diagram, was calculated using Spearman's technique that determines the worth of -0.9487 with negative coefficient and terribly sturdy correlation doesn't -linear.

The most significant ends up in Pearson's correlation calculation for density contains mineral percentages of volcanic rock and iron hydroxide. The numerical results of Zeolite (-0.4324) showed moderate negative linear correlation however these results were discarded due to solely 2 samples experiencing this mineral. The volcanic glass obtained moderate negative linear correlation with value -0.3483 and iron hydroxide value of zero.3069 with moderate negative linear correlation. The Scatter Diagrams for these two minerals will not favor conclusive interpretations of the degree of correlation between the variables. The correlation between the density and particle size and other minerals percentages expressed degree of correlation weak conclusion to these variables didn't influence the ultimate results of the mass specific. The sum of secondary minerals showed negative linear correlation constant of -0.4456 being classified as moderate. The dispersion diagrams follow the trend calculations by the Pearson method.

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