Advanced EViews #4 - Vector Autoregressive (VAR) Modeling

Understanding Econometrics Modelling concepts pertaining to Finance and Financial markets by applying concepts of Volatility Modelling & Autoregressive Conditional Heteroscedasticity

Full Star Full Star Full Star Full Star Empty Star  13
  |   1267 Learners
  |   2 - 6 hours  4 Hrs
  |   20 Lectures
  |   Expert  Expert
Advanced EViews #5 (Modeling Longrun Relationships) - Stationarity And Unit Root Testing

This course covers theoretical aspects of Stationarity and unit root testing concepts, and Dickey-Fuller tests. It discusses test cases with/without intercept and trends, and its interpretation.

Full Star Full Star Full Star Full Star Empty Star  13
  |   1240 Learners
  |   Upto 2 hours  2 Hrs
  |   12 Lectures
  |   Expert  Expert
Advanced EViews #6 (Modeling Longrun Relationships) - CoIntegration Testing

This course covers theory on Cointegration concepts, and Johanssen technique, its implementation and interpretation in Eviews.

Full Star Full Star Full Star Full Star Empty Star  13
  |   1273 Learners
  |   Upto 2 hours  2 Hrs
  |   10 Lectures
  |   Expert  Expert
Advanced EViews #7 - Volatility & ARCH Modeling

Understanding Econometrics Modelling concepts pertaining to Finance and Financial markets by applying concepts of Volatility Modelling & Autoregressive Conditional Heteroscedasticity.

Full Star Full Star Full Star Full Star Half Star  13
  |   1775 Learners
  |   2 - 6 hours  6 Hrs
  |   33 Lectures
  |   Expert  Expert
EViews Series (Module #1) - Econometrics Modeling

This course aims to provide basic to intermediate skills on implementing Econometrics/Predictive modeling concepts using Eviews software. Whilst its important to develop understanding of econometrics /quantitative modeling concepts, its equally important to be able to implement it using suitable software packages.

Full Star Full Star Full Star Full Star Half Star  13
  |   2104 Learners
  |   Upto 2 hours  1 Hrs
  |   3 Lectures
  |   Appropriate for all  All Levels
EViews Series (Module #2) - Descriptive Statistics

Descriptive Statistics, Means, Standard Deviation and T-test – This course explains descriptive statistics concepts which will act as building blocks to subsequent courses.

Full Star Full Star Full Star Full Star Half Star  13
  |   2049 Learners
  |   Upto 2 hours  2 Hrs
  |   10 Lectures
  |   Appropriate for all  All Levels
EViews Series (Module #3) - Correlation Techniques

In this course, you will learn about Generating Correlation matrix in Eviews. Correlation techniques explain relationships across variables and are important in explain the model fitment in regression courses.

Full Star Full Star Full Star Full Star Empty Star  13
  |   2073 Learners
  |   Upto 2 hours  2 Hrs
  |   12 Lectures
  |   Appropriate for all  All Levels
EViews Series (Module #4) - Regression Modeling

The core objective of this course is to provide skills in understand the regression model and interpreting it for predictions. The associated parameters of the regression model will be interpreted and tested for significance and test the goodness of fit of the given regression model. The course covers linear and multiple regression modeling

Full Star Full Star Full Star Full Star Empty Star  13
  |   2168 Learners
  |   2 - 6 hours  4 Hrs
  |   21 Lectures
  |   Appropriate for all  All Levels
MATLAB - Advance Your Career with MATLAB Programming

In this course you will learn about fundamentals of matlab, all about array and linear equation, polynomial equation, control flow, probability and statistical data, plot the outcome and symbolic equation. Themes of data analysis, visualization, modeling, and programming are explored throughout the course.

Full Star Full Star Full Star Full Star Half Star  12
  |   3954 Learners
  |   6 - 12 hours  9 Hrs
  |   51 Lectures
  |   Appropriate for all  All Levels
EViews

Understanding Econometrics Modelling concepts pertaining to Finance and Financial markets using Eviews.

Full Star Full Star Full Star Full Star Empty Star  7
  |   3646 Learners
  |   6 - 12 hours  8 Hrs
  |   46 Lectures
  |   Appropriate for all  All Levels
QM for Windows - Statistical Analysis Using QM

The course intends to enhance understanding of problem-solving and quantitative analysis through QM 2 software package.

Full Star Full Star Full Star Full Star Empty Star  14
  |   3989 Learners
  |   Upto 2 hours  2 Hrs
  |   13 Lectures
  |   Intermediate  Intermediate
Financial Analytics

Through this financial analytics training you shall be understanding various Financial and Statistical Formulas & its Analysis with practical examples.

Full Star Full Star Full Star Full Star Empty Star  13
  |   4317 Learners
  |   Upto 2 hours  2 Hrs
  |   12 Lectures
  |   Appropriate for all  All Levels
Regression Modeling with Minitab

Understanding Regression Modelling concepts and its applications across domains viz. Finance, Pharma and Medicine.

Full Star Full Star Full Star Full Star Empty Star  8
  |   7254 Learners
  |   6 - 12 hours  12 Hrs
  |   67 Lectures
  |   Intermediate  Intermediate
Multinomial Regression in SPSS

This course is for you to understand multinomial or polynomial regression modelling concepts of quadratic nature with equation of form Y = m1*X1 + m2*X22 + C + p1B1 + p2B2 + ….. pnBn

Full Star Full Star Full Star Full Star Empty Star  15
  |   4802 Learners
  |   2 - 6 hours  3 Hrs
  |   14 Lectures
  |   Intermediate  Intermediate
Logistic Regression in SPSS

Through this training we will provide you the necessary skills in understanding the logistic regression model and interpreting it for predictions. You shall be understanding binary/dummy variables concepts for logistic regressions.

Full Star Full Star Full Star Full Star Empty Star  14
  |   4862 Learners
  |   2 - 6 hours  3 Hrs
  |   14 Lectures
  |   Intermediate  Intermediate
Multiple Regression Modeling using SPSS

Through this training we will provide you the necessary skills in understanding the multiple regression model and interpreting it for predictions. The associated parameters of the regression model will be interpreted and tested for significance and test the goodness of fit of the given regression model

Full Star Full Star Full Star Full Star Empty Star  5
  |   4983 Learners
  |   2 - 6 hours  3 Hrs
  |   16 Lectures
  |   Expert  Expert
Correlation Techniques Using SPSS

This course on comparable company analysis will help the learner in getting a general overview and understand where comparable comps places itself in the bigger picture of valuation of stocks.

Full Star Full Star Full Star Full Star Empty Star  7
  |   5197 Learners
  |   Upto 2 hours  2 Hrs
  |   12 Lectures
  |   Intermediate  Intermediate
Linear Regression Modeling Using SPSS

Through this training we will provide you the necessary skills in understanding the linear regression model and interpreting it for predictions.

Full Star Full Star Full Star Full Star Empty Star  9
  |   5198 Learners
  |   2 - 6 hours  4 Hrs
  |   23 Lectures
  |   Intermediate  Intermediate
Descriptive Statistics using SPSS

In this course, you will be learning the Interpretation of descriptive statistics and t- values along with the implementation on example/sample datasets using SPSS

Full Star Full Star Full Star Full Star Empty Star  5
  |   5318 Learners
  |   Upto 2 hours  2 Hrs
  |   9 Lectures
  |   Intermediate  Intermediate
Predictive Modeling and Implementation Using MS Excel

Understanding predictive analytics concepts of regression modelling, correlation and implementing them using MS Excel.

Full Star Full Star Full Star Full Star Half Star  12
  |   5872 Learners
  |   Upto 2 hours  1 Hrs
  |   7 Lectures
  |   Intermediate  Intermediate
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“In "Microsoft Excel 2016 Basic course", i had learnt about the basic things, in working with Microsoft Excel 2016. There was a basic introduction, open Excel with different ways, many ribbons and quick access toolbar, data transfer from word to Excel, different types of calculation, different types of formula, and there are many more topics which I learnt with basic course of Microsoft Excel 2016. thank you!

— Riddhi Awadhalal Gupta

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