138 results found for correlation analysis

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By Riya Jain & Priya Chetty on September 19, 2019 3 Comments

Correlation is a statistical measure that helps in determining the extent of the relationship between two or more variables or factors.

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By Divya Narang & Priya Chetty on July 8, 2019 2 Comments

E- Views offer an impressive toolkit that involves the series or the group of series that allows estimating panel data analysis ranging from the simplest to the complex types. Performing data analysis in E-views is easier to understand as all the necessary statistical modelling can be performed by estimating the regression equation.

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By Avishek Majumder & Priya Chetty on April 10, 2019 1 Comment

Momentum analysis is mainly done to measure the rate of rising or fall in stock prices. It is a method to show the trend of daily stocks and prices over time.

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There different instruments to collect primary data and the most widely used is the questionnaire in a survey method. Correlation and regression tests are two of the basic statistical tools that are widely applied to analyze data.

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By Avishek Majumder on November 27, 2018 No Comments

Biomarker discovery starts with a small number of samples in the form of preclinical exploratory studies to identify promising biomarkers form a pool of diseased and non-diseased groups.

 

This article of the module explains how to perform panel data analysis using STATA. In the case of panel data, the observations are present in time and space dimensions. For instance, a survey of the same cross-sectional unit such as firm, country or state over time.

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The previous article showed how to initiate the AutoRegressive Conditional Heteroskedasticity (ARCH) model on a financial stock return time series for period 1990 to 2016. It showed results for stationarity, volatility, normality and autocorrelation on a differenced log of stock returns.

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By Divya Dhuria & Priya Chetty on October 4, 2018 4 Comments

Volatility only represents a high variability in a series over time.This article explains the issue of volatility in data using Autoregressive Conditional Heteroscedasticity (ARCH) model. It will identify the ARCH effect in a given time series in STATA.

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