scholarly journals A Discriminant Model For Skill Oriented Prediction of Female Cricketers Depending Upon Selected Performance Parameters

2021 ◽  
Vol 21 (4) ◽  
pp. 293-298
Author(s):  
Sapna Mandoli ◽  
Deepak Sharma ◽  
Hem Chandra Joshi
Keyword(s):  
Discriminant Analysis ◽  
Total Variation ◽  
Muscle Mass ◽  
Statistical Technique ◽  
Performance Parameters ◽  
Performance Variables ◽  
Multivariate Technique ◽  
Discriminant Model ◽  
Shoulder Diameter ◽  
Variation Explained

Research Purpose. The study aimed to develop a discriminant model for cricketers on the basis of physiological & anthropometric variables. Material and Methods. The study included sixty female seniors BCCI board players representing five different states with mean age 23.4 ± 2.03, mean height 152.1 ± 3.44, and mean weight 52.4 ± 4.21. A multivariate technique was used to predict the cricket performance by classifying the players into batsmen and pace bowlers on the basis of selected physiological & anthropometrical variables. Results. All the assumptions were positively full-filled (Shapiro-Wilk test p > 0.05 and F = 8.121, p = 0.264 for Box’sM test) for applying discriminant analysis to develop the model. A total of eleven performance variables were initially selected for the study and after applying the stepwise statistical technique of discriminant analysis, the model selected certain variables, namely Muscle Mass (1.311), Fat (-0.182) & Shoulder Diameter (0.292) and showed its effectiveness as the Eigenvalue for the fit model was 0.848. Conclusion. A discriminant function F1 = -29.531 + (1.311 × Muscle Mass) + (-0.182 × Fat) + (0.292 × Shoulder Diameter) was developed. The percentage of total variation explained by the model was 71.9%. A total of 93.2% of the observations were correctly classified using the proposed discriminant model.

scholarly journals Right choice of a method for determination of cut-off values: A statistical tool for a diagnostic test

2014 ◽  
Vol 5 (3) ◽  
pp. 30-34 ◽  
Author(s):  
Balkishan Sharma ◽  
Ravikant Jain
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Diagnostic Test ◽  
Roc Curve ◽  
Traditional Method ◽  
Statistical Technique ◽  
Curve Analysis ◽  
Operating Characteristics ◽  
Roc Curve Analysis

Objective: The clinical diagnostic tests are generally used to identify the presence of a disease. The cutoff value of a diagnostic test should be chosen to maximize the advantage that accrues from testing a population of human and others. When a diagnostic test is to be used in a clinical condition, there may be an opportunity to improve the test by changing the cutoff value. To enhance the accuracy of diagnosis is to develop new tests by using a proper statistical technique with optimum sensitivity and specificity. Method: Mean±2SD method, Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been discussed with their respective applications. Results: The study highlighted some important methods to determine the cutoff points for a diagnostic test. The traditional method is to identify the cut-off values is Mean±2SD method. Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been proved to be beneficial statistical tools for determination of cut-off points.Conclusion: There may be an opportunity to improve the test by changing the cut-off value with the help of a correctly identified statistical technique in a clinical condition when a diagnostic test is to be used. The traditional method is to identify the cut-off values is Mean ± 2SD method. It was evidenced in certain conditions that logistic regression is found to be a good predictor and the validity of the same can be confirmed by identifying the area under the ROC curve. Abbreviations: ROC-Receiver operating characteristics and DA-Discriminant Analysis. Asian Journal of Medical Science, Volume-5(3) 2014: 30-34 http://dx.doi.org/10.3126/ajms.v5i3.9296      

Assessment of Urban Road Traffic Safety Based on Bayes Discriminant Analysis Method

2013 ◽  
Vol 639-640 ◽  
pp. 544-547
Author(s):  
Chang Ping Wen ◽  
Qing Qing Tian
Keyword(s):  
Discriminant Analysis ◽  
Traffic Safety ◽  
Evaluation Method ◽  
Road Traffic ◽  
Urban Road ◽  
Discriminant Model ◽  
Road Traffic Safety ◽  
Normal Populations ◽  
Proposed Model ◽  
Bayes Discriminant Analysis

Bayes discriminant analysis theory (BDAT) is used to create an evaluation method to determine the condition of urban road traffic safety. The resulting Bayes discriminant model (BDM) is designed to strictly adhere to BDAT. Three indexes including death ratio per ten thousand vehicles, death ratio per hundred thousand bicycles and death ratio per hundred thousand citizens are selected as the factors in the analysis of urban road traffic safety. The grade of condition of urban road traffic safety is divided into three grades that are regarded as three normal populations in Bayes discriminant analysis. Bayes discriminant functions rigorously constructed through training a set of samples are employed to compute the Bayes function values of the evaluating samples, and the maximal function value is used to judge which population the evaluating sample belongs to. The optimality of the proposed model is verified by back-substitution method. The study shows that the prediction accuracy of the proposed model is 100% and could be used in practice.

scholarly journals PENENTUAN SEBARAN SPASIAL PENCEMARAN AIR DI KOTA PONTIANAK MENGGUNAKAN ANALISIS DISKRIMINAN DUA KELOMPOK

2019 ◽  
Vol 12 (2) ◽  
pp. 226
Author(s):  
Muhammad Fikri ◽  
Naomi Nessyana Debataraja ◽  
Dadan Kusnandar
Keyword(s):  
Discriminant Analysis ◽  
Sustainable Development Goals ◽  
Oxygen Demand ◽  
Pollution Index ◽  
Pollution Level ◽  
Accuracy Rate ◽  
Discriminant Model ◽  
Development Goals ◽  
Independent Variable ◽  
Rate Method

Clean water is one point of sustainable Development Goals (SDGs), so to keep indicator water quality must be determine every period. The Discriminant analysis is an analysis of dependence that is used to classify objects into several categories. The purpose of this study were to determine the discriminant model that consist of dominant factors of water pollution. Samples were taken from 42 locations in the surrounding area of Pontianak City. The sample were analyzed in the laboratory for the contents of ferrum (Fe), dissolved oxygen (DO), biochemical oxygen demand (BOD). Width of the river were also considered is an independent variable. The methodology includes determining the pollution index that will be used as dependent variable, testing the assumption of multivariate normality and similarity of the covariance variance, conducting the discriminant analysis classification process using the Apparent Error Rate method. The pollution level of each location was visualized in a map. The resulting discriminant model has an accuracy rate of 69%.

ANALISIS KINERJA KEUANGAN SEBAGAI ALAT PREDIKSI KEBANGKRUTAN DENGAN MODEL DISKRIMINAN

2015 ◽  
Vol 10 (2) ◽  
pp. 97
Author(s):  
Yulinartati Yulinartati
Keyword(s):  
Discriminant Analysis ◽  
Profit Margin ◽  
Return On Assets ◽  
Current Ratio ◽  
Return On Equity ◽  
Discriminant Model ◽  
Operating Profit ◽  
Net Profit ◽  
Equity Ratio ◽  
Turn Over

The purpose of this study was to determine whether the Current Ratio (CR), Debt Equity Ratio (DER), Total Assets Over Turen (TATO), net profit margin (NPM), Debt to Assets Ratio (DAR), Return on Assets (ROA) , Return on Equity (ROE), Gross Profit Margin (GPM), Operating Profit Margin (OPM) influential in distinguishing healthy firms and perusahaa bankruptcy discriminant model. Based on discriminant analysis of known groups of healthy companies and a group of companies that went bankrupt differ significantly, from 9 (nine) variables are in use only 4 (four) variable Current Ratio, Debt Equity Ratio, Net Profit Margin, and Gross Profit Margin is selected and able to differentiate healthy companies and companies go bankrupt, while the 5 (five) of the variables, Turn Over Total Assets, Debt to Assets Ratio, Return on Assets, Return on Assets, and Operating Profit Margin are not able to differentiate healthy and bankrupt companies. Keywords: Current Ratio ,Debt Equity Ratio, Total Assets Turen Over , Net profit Margin , Return on Assets, Return on Equity

scholarly journals Broiler chick performance using Saccharomyces cerevisiae yeast cell wall as an anti-mycotoxin additive

2021 ◽  
Vol 66 (No. 2) ◽  
pp. 65-72
Author(s):  
Vinícius Machado dos Santos ◽  
Gabriel da Silva Oliveira ◽  
Cristina Amorim Ribeiro de Lima ◽  
Fernando Augusto Curvello
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Cell Wall ◽  
Yeast Cell ◽  
Broiler Chicken ◽  
Live Weight ◽  
Yeast Cell Wall ◽  
Performance Parameters ◽  
Feed Conversion ◽  
Performance Variables ◽  
Aflatoxin B

The objective of this study was to evaluate the effects of using the Saccharomyces cerevisiae yeast cell wall (YCW) as an aflatoxin B<sub>1 </sub>(AFB<sub>1</sub>) adsorbent in broiler chicken feed on performance and carcass characteristics. The present study used a randomized complete block with four treatments in a 2 (with or without AFB<sub>1</sub>) × 2 (with or without YCW) factorial design. No interaction effect (P &gt; 0.05) between AFB<sub>1</sub> and YCW was found on the studied performance variables. The addition of YCW to the diets stimulated the feed intake of chickens during 1–21 days of age. However, YCW did not significantly increase (P &gt; 0.05) weight gain nor did it change feed conversion. The presence of AFB<sub>1</sub> in the diet did not affect (P &gt; 0.05) performance parameters. The addition of YCW to the feed containing AFB<sub>1</sub> significantly increased (P &lt; 0.05) the post-fasting live weight (781.12 g), chilled carcass weight (554.41 g), and leg weight (163.34 g) compared to feed without AFB<sub>1</sub> and YCW (764.84 g; 533.41 g; 161.88 g), feed with only YCW (764.22 g; 546.87 g; 159.34 g), and feed with only AFB<sub>1</sub> (735.41 g; 510.56 g; 152.75 g). In conclusion, YCW effectively reduced some of the deleterious effects of AFB<sub>1</sub> in broilers.

scholarly journals Alifta Ainurrochmah, Perbandinga

2020 ◽  
Vol 11 (2) ◽  
pp. 37
Author(s):  
Alifta Ainurrochmah ◽  
Memi Nor Hayati ◽  
Andi M. Ade Satriya
Keyword(s):  
Discriminant Analysis ◽  
Naive Bayes ◽  
Insurance Premium ◽  
Naïve Bayes ◽  
Fisher Discriminant Analysis ◽  
Bayes Method ◽  
Premium Payment ◽  
Multivariate Technique ◽  
Fisher’S Discriminant Analysis ◽  
Naive Bayes Method

Classification is a technique to form a model of data that is already known to its classification group. The model was formed will be used to classify new objects. Fisher discriminant analysis is multivariate technique to separate objects in different groups. Naive Bayes is a classification technique based on probability and Bayes theorem with assumption of independence. This research has a goal to compare the level of classification accuracy between Fisher's discriminant analysis and Naive Bayes method on the insurance premium payment status customer. The data used four independent variables that is income, age, premium payment period and premium payment amount. The results of misclassification using the APER (Apparent Rate Error) indicate that the naive Bayes method has a higher level of accuracy is 15,38% than Fisher’s discriminant analysis is 46,15% on the insurance premium payment status customer.

scholarly journals Clients’ selection of auditors: evidence from the Athens stock exchange

2015 ◽  
Vol 3 (2) ◽  
pp. 156
Author(s):  
Anastasia Maggina
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Stock Exchange ◽  
Audit Fees ◽  
Statistical Technique ◽  
Financial Ratios ◽  
Institutional Factors ◽  
Data Set ◽  
Second Tier ◽  
Selection Of

<p>The auditing profession is at a crossroad worldwide. It currently faces many challenges especially in Greece where auditor rotation has been instituted as mandatory by EU regulation and the auditing profession is going to be fully liberalized (no limits on audit fees) . Given the Greek environment, it is important to investigate how client companies select auditors. In this study we address three questions. First, can selection of auditors be forecasted? Second, which statistical technique better fits the data set? Third, are there differences in firms’ financial ratios as well as institutional factors that affect auditor choice? Clients’ selection of auditors is considered in a research context using discriminant analysis and logistic regression. The discriminating factors between the two groups of companies include some firm financial ratios and institutional factors: QATA(Quick Assets/Total Assets) when using one year data, and QATA(Quick Assets/Total Assets) and SHAREHOLD (level of shareholdings) when using two year data. Prediction accuracy is close to 60.0 percent using discriminant analysis and around 80.0 percent using logistic regression. The contribution of this study is that it discriminates between the two groups of companies (Big Four versus second-tier or local auditing firms) in an IFRS environment.</p>

Complete Kernal Fisher Discrimination Analysis

2006 ◽  
pp. 235-257
Author(s):  
David Zhang ◽  
Xiao-Yuan Jing ◽  
Jian Yang
Keyword(s):  
Discriminant Analysis ◽  
Theoretical Perspective ◽  
Statistical Technique ◽  
Experimental Results ◽  
Fisher Discriminant Analysis ◽  
Discrimination Analysis ◽  
Fisher Discriminant ◽  
Kernel Fisher Discriminant Analysis ◽  
Algorithm Framework

This chapter introduces a complete kernel Fisher discriminant analysis (KFD) that is a useful statistical technique applied to biometric application. We first describe theoretical perspective of KPCA. Then, a new KFD algorithm framework, KPCA plus LDA, is given. Afterwards, we discuss the complete KFD algorithm. Finally, the experimental results and chapter summary are given.

A discriminant analysis of organizational performance variables.

1973 ◽  
Vol 58 (3) ◽  
pp. 368-371 ◽  
Author(s):  
Herbert H. Hand ◽  
William R. LaFollette
Keyword(s):  
Discriminant Analysis ◽  
Organizational Performance ◽  
Performance Variables

In-Water Resisted Swim Training for Age-Group Swimmers: An Evaluation of Training Effects

2018 ◽  
Vol 30 (1) ◽  
pp. 124-131 ◽  
Author(s):  
Kosuke Kojima ◽  
Christopher L. Brammer ◽  
Tyler D. Sossong ◽  
Takashi Abe ◽  
Joel M. Stager
Keyword(s):  
Skeletal Muscle ◽  
Muscle Mass ◽  
Repeated Measures ◽  
Skeletal Muscle Mass ◽  
Age Group ◽  
Performance Variables ◽  
Swim Performance ◽  
Time Interaction ◽  
Repeated Measures Analysis ◽  
And Performance

Purpose:The purpose of this study is to compare the efficacy of resisted sprint swim training with that of nonresisted sprint swim training on 50-m freestyle competition time (Vmax50) in age-group swimmers.Methods:Twenty-four age-group swimmers (age 10.6–14.9 y) were divided into resisted or nonresisted sprint swim training groups and completed a sprint swim training intervention 2 times per week for 10 weeks. Repeated 10-m sprints with progressively increasing resistance were used to determine measures of swim power. Skeletal muscle mass was estimated using B-mode ultrasound. Maturity status was estimated using predicted adult height (%Htadult) and maturity offset.Results:A 2-way repeated-measures analysis of variance revealed no group × time interaction for measured variables. Vmax50 was correlated with skeletal muscle mass and swim power variables, but no significant relationship was found between relative changes in these variables. Estimated maturity status (%Htadult) appeared to be associated with initial measures of swim power and performance variables.Conclusions:Ten weeks of resisted sprint swim training was not any more effective than nonresisted sprint swim training at improving sprint swim performance in age-group swimmers.

Sign in / Sign up

Export Citation Format

Share Document