Vikas J. Profile

0.0

(0 reviews)

You're now following

Error following user.

This user does not allow users to follow them.

You are already following this user.

Your membership plan only allows 0 follows. Upgrade here.

Successfully unfollowed

Error unfollowing user.

You have successfully recommended

Error recommending user.

Something went wrong. Please refresh the page and try again.

Email successfully verified.

$20 USD / hour

calgary,

canada

$20 USD / hour

It's currently 1:12 AM here

Joined May 24, 2020

0 Recommendations

Vikas J.

@vjangra49

0.0

(0 reviews)

0.0

$20 USD / hour

calgary,

canada

$20 USD / hour

N/A

Jobs Completed

N/A

On Budget

N/A

On Time

N/A

Repeat Hire Rate

Statistician/ Biostatistician/ Statistical Analyst

An accomplished Statistician with 5+ years of experience and a strong background in statistical analysis, data modelling, and hypothesis testing. Proficient in utilizing statistical software and programming languages to extract meaningful insights from complex or large data sets. Known for precision, analytical rigor, and ethical data practices. Well-versed in regression analysis, time series analysis, Bayesian statistics, and data visualization. A valuable resource for organizations seeking data-driven decision-making and strategic growth. Expertise in both descriptive and inferential statistics.

See all Statisticians in Canada

Contact Vikas J. about your job

Reviews

Changes saved

No reviews to see here!

Experience

ethica CRO

Apr 2023 - Nov 2023 (7 months, 1 day)

Developed plans for statistical analyses, outlining methodologies, and specifying appropriate statistical tests or models for data interpretation. Utilized statistical programming language (e.g., SAS,) to analyze and manipulate large datasets. Ensured the statistical aspects of clinical trials adhere to regulatory standards and guidelines. Provided Statistical expertise for design, analysis, and reporting of clinical trials. Generated statistical tables, listings and figures (TLFs).

National institute of Medical Statistics

Mar 2022 - Mar 2023 (1 year)

Advised on data sampling and collection procedures to ensure the highest data integrity. Conduct research into the mathematical basis of the science of statistics Develop statistical methodology and guide on the practical application of statistical methodology. Utilized statistical software such as SPSS, STATA and SAS to track and analyze the data. Investigated and conducted studies on the Regression, Correlation and ANOVA.

National AIDS control Organisation

Mar 2021 - Mar 2022 (1 year)

Compiled tables, charts, and graphs, summarized statistics for integration in research papers and reports. Prepared statistical analysis plans and provided statistical interpretation for graphs, tables and charts. Processed data using statistical software to conduct basic analyses of trends in support of research planning and preparing research protocols. Assisted in manuscripts writing and preparation of publications and presentations. Assisted in dissemination of research outcomes.

Education

Ph.D statistics

Panjab University,

India

2017 - 2023

(6 years)

Msc. Statistics

Panjab University,

India

2015 - 2017

(2 years)

Publications

Assessment of Fine Particulate Matter for Port City of Eastern Peninsular India Using Gradient

MDPI

An assessment and prediction of PM2.5 for a port city of eastern peninsular India is presented. Fifteen machine learning (ML) regression models were trained, tested and implemented to predict the PM2.5 concentration. The predicting ability of regression models was validated using air pollutants and meteorological parameters as input variables collected from sites located at Visakhapatnam, a port city on the eastern side of peninsular India, for the assessment period 2018–2019.

A Bayesian estimation of the Gini index and the Bonferroni index for the Dagum distribution.

Statistics in Transition new series

Bayesian estimators and highest posterior density credible intervals are obtained for two popular inequality measures, viz. the Gini index and the Bonferroni index in the case of theDagum distribution. The study considers informative and non-informative priors, i.e. the Mukherjee-Islam prior and the extension of Jeffrey’s prior, respectively, under the presumption of the Linear Exponential (LINEX) loss function.