Analysing the concrete compressive strength using Pearson and Spearman

Spearman's rank relationship coefficient is a nonparametric (dispersion free) rank measurement. Spearman's coefficient is not a measure of the direct relationship between two factors, as a few ”analysts” proclaim. Pearson's relationship coefficient is the covariance of the two factors separated by the result of their standard deviations. The possibility of the paper is to look at the estimations of Pearson's concrete compressive strength coefficient and Spearman's rank relationship coefficient and in addition their factual hugeness for various arrangements of information depicting provincial records of the financial advancement. In this, the Spearman correlation coefficient is based on the ranked values for each variable rather than the raw data. Spearman correlation is often used to evaluate relationships involving ordinal variables. The Pearson and Spearman's method is compared with the rank coefficient in the concrete compressive strength.

[1]  W. Micah Hale,et al.  Effect of concrete compressive strength on transfer length , 2016 .

[2]  P. Maca,et al.  Development of Ultra High Performance Fiber Reinforced Concrete mixture , 2012, 2012 IEEE Symposium on Business, Engineering and Industrial Applications.

[3]  Chandra Segar Thirumalai,et al.  SPANNING TREE APPROACH FOR ERROR DETECTION AND CORRECTION , 2017 .

[4]  Chandra Segar Thirumalai PHYSICIANS DRUG ENCODING SYSTEM USING AN EFFICIENT AND SECURED LINEAR PUBLIC KEY CRYPTOSYSTEM (ESLPKC) , 2016 .

[5]  Chandra Segar Thirumalai,et al.  SYSTEM USING BASE 128 ENCODING SCHEME , 2017 .

[6]  Mohammad Ali Hadianfard,et al.  Prediction of lightweight aggregate concrete compressive strength using ultrasonic pulse velocity test through gene expression programming , 2016 .

[7]  Frank Klawonn,et al.  A Bayesian Network for the Definition of Probability Models for Compressive Strength of Concrete Homogeneous Population , 2017 .

[8]  H. Oh,et al.  Estimating the Compressive Strength of High-Strength Concrete Using Surface Rebound Value and Ultrasonic Velocity , 2016 .

[9]  R. Vijayaragavan,et al.  Pell's RSA key generation and its security analysis , 2013, 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT).

[10]  H. Toutanji,et al.  BEHAVIOR OF CONCRETE COLUMNS CONFINED WITH FIBER REINFORCED POLYMER TUBES , 1999 .

[11]  Experimental research on the flexural strength of recycled coarse aggregate concrete , 2010, 2010 International Conference on Mechanic Automation and Control Engineering.

[12]  Faezehossadat Khademi,et al.  EVALUATION OF CONCRETE COMPRESSIVE STRENGTH USING ARTIFICIAL NEURAL NETWORK AND MULTIPLE LINEAR REGRESSION MODELS , 2016 .

[13]  Chandrasegar Thirumalai,et al.  Physicians medicament using linear public key crypto system , 2016, 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT).

[14]  Chandrasegar Thirumalai,et al.  An assessment framework for Precipitation decision making using AHP , 2017, 2017 11th International Conference on Intelligent Systems and Control (ISCO).

[15]  Chandra Segar Thirumalai REVIEW ON THE MEMORY EFFICIENT RSA VARIANTS , 2017 .

[16]  Min-Yuan Cheng,et al.  High-performance Concrete Compressive Strength Prediction using Time-Weighted Evolutionary Fuzzy Support Vector Machines Inference Model , 2012 .

[17]  Jui-Sheng Chou,et al.  Optimizing the Prediction Accuracy of Concrete Compressive Strength Based on a Comparison of Data-Mining Techniques , 2011, J. Comput. Civ. Eng..

[18]  Chandrasegar Thirumalai,et al.  One-Dimension Force Balance System for Hypersonic Vehicle an experimental and Fuzzy Prediction Approach , 2018 .

[19]  H. Oh,et al.  An Empirical Estimation Procedure of Concrete Compressive Strength Based on the In-Situ Nondestructive Tests Result of the Existing Bridges , 2016 .

[20]  Ravindra K. Dhir,et al.  Establishing a relationship between modulus of elasticity and compressive strength of recycled aggregate concrete , 2016 .