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One Day National Level Workshop on WrapPLS – A Statistical Tool for Analysis for Management, Commerce, Economics and Social Science Researchers 07.04.2017-Organised by DEPARTMENT OF BUSINESS ADMINISTRATION DIRECTORATE OF DISTANCE EDUCATION MADURAI KAMARAJ UNIVERSITY MADURAI -625 021.

WarpPLS 5.0:

WarpPLS is powerful Structural Equation Modeling (SEM) Software.

Warp PLS is easy to use with step by step interface guide. It has got the

provision for correcting sampling errors and standardising the data. It

has got easily comprehensive graphical outputs for structural equation

modelling. Warp PLS implements classic (composite-based) as well as

factor-based PLS algorithms. It identifies nonlinear relationships, and

estimates path coefficients accordingly. It also models linear

relationships, using classic and factor-based PLS algorithms, reflective

and formative variables, as well as moderating effects. Warp PLS

calculates P values, model fit and quality indices, and full collinearity

coefficients. It calculates effect sizes and Q-squared predictive validity

coefficients. It also calculates indirect effects for paths with 2, 3 etc.

Segments, as well as total effects and calculates several causality

assessment coefficients. It provides a number of graphs, including

zoomed 2D graphs, and 3D graphs.

There are two main advantages of using Warp PLS to conduct a

multiple regression analysis. The advantages are over a traditional

multiple regression analysis, where the independent and dependent

variables are measured through single indicators. With Warp PLS, this

would be implemented through the creation of "latent" variables that

would each be associated with a single indicator, which means that

they would not be true latent variables in the sense normally assumed

in structural equation modelling.

The first advantage is that the calculation of P values with WarpPLS is

based on a nonparametric algorithm, re-sampling, and thus does not

require that the variables be normally distributed. A traditional

multiple regression analysis, on the other hand, requires that the

variables be normally distributed. In this sense, WarpPLS can be seen

as conducting a robust, or nonparametric, multiple regression analysis.

This first advantage assumes that all one is doing is a plain linear

analysis with WarpPLS, for which one would use the algorithms PLS

Regression or Robust Path Analysis. The second advantage is that Warp

PLS allows for nonlinear relationships between the independent and

dependent variables to be analyzed. This provides a much richer view of

the associations between variables, and sometimes leads to path

coefficients that are different from (often higher than) those obtained

through a linear analysis (as in a traditional multiple regression analysis).

The nonlinear analysis algorithms available are Warp3 PLS Regression

(which yields S curves) and Warp2PLS Regression (which yields U

curves).

Use of WarpPLS:

Warp PLS substitutes multiple regression analysis and ANOVA. It

measures the relationship between elements and constructs, latent

variables etc. It can be used to measure the level of influence of

independent variables on the dependent variables, and the significance

of independent variables. The percentages of dependent variables are

also explained by the independent variables collectively. This may not

be useful for substituting analysis like t-test, chi-square test etc.

BRIEF PROFILE OF THE RESOURCE PERSON

Dr. Joseph Mathews Cherukara, B. Sc., MBA, M. Phil, Ph. D.

He has long experience in teaching

management students and has been

Adjunct Faculty for Business Management,

Marketing Management, International

Business, Entrepreneurship Development,

etc. in different business schools and

entrepreneurship development programmes. He also teaches research

methodology and a specialist in WarpPLS software for data analysis.

He is approved by Entrepreneurship Development Institute of India as

Faculty for Faculty Development Program in EDP. He has got 40+

years of entrepreneurial experience in different industries. He has

long experience as management consultant and was an approved

consultant by K-BIP, Industries Department, Government of Kerala for

management and cluster development. He is Graduate in Science, Post

Graduate in Management, and M. Phil in Entrepreneurship (MKU)

and Ph. D. (CUSAT) in the topic ‘Factors Leading to Entrepreneurial

Success—Study based on MSMEs of Kerala’. He has published several

papers in management and entrepreneurship, through various

national and international conferences, and listed journals. The paper

titled ‘Medical Tourism in Kerala: Challenges and Scope’ has wide

references from around the world and 15 citations as per

scholar.google. He is a popular author in global scientific author’s

societies such as Academia.edu (US) as well as Research Gate

(Germany) and was listed by Academia.edu among top 1% global

authors for 30 days in Jan-Feb 2017.

ORGANIZING SECRETARY

Dr.R.MENAKA

Assistant Professor,

Department of Management Studies,

Directorate of Distance Education,

Madurai Kamaraj University,

Palkalai Nagar, Madurai - 625 021

Mail Your Confirmation to : drrmmkudde@gmail.com

Contact if any : 9944949430

FEE DETAILS AND INSTRUCTIONS:

Corporate Delegates : Rs.1000/-

Faculty Members : Rs.750/-

Research Scholars and Students : Rs.500/-

? Fee includes Workshop Kit, Lunch and High-Tea.

? Strictly Last date for Registration: March’29, 2017.

? All should bring their laptop for practice.

More Information Please Click here

Source:Information(s) Provided By

Dr.R.MENAKA

Assistant Professor,

Department of Management Studies,

Directorate of Distance Education,

Madurai Kamaraj University,

Palkalai Nagar, Madurai - 625 021

Mail Your Confirmation to : drrmmkudde@gmail.com

Contact Mobile No : 9944949430

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