• GURINDER KAUR

Quantitative research relies heavily on the effective statistical treatment of data to extract meaningful insights and inform decision-making. This abstract outlines a comprehensive approach to statistical data analysis, encompassing descriptive statistics, inferential statistics, and advanced analytical techniques. The methodology includes data visualization, regression analysis, hypothesis testing, and confidence intervals to identify patterns, trends, and correlations. Additionally, techniques such as ANOVA, t-tests, factor analysis, and cluster analysis are employed to examine complex relationships and group differences. The application of non-parametric and parametric tests, data transformation, and outlier detection ensures robust and reliable findings. This statistical treatment of data provides a foundation for rigorous quantitative research, enabling researchers to draw valid conclusions and contribute meaningfully to their field of study.

Descriptive statistics, Inferential statistics, Data visualization, Regression analysis, Hypothesis testing, Confidence intervals, Significance testing

"Statistical Treatment of data for Quantitative Research", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 7, page no.c521-c527, July-2024, Available :http://www.jetir.org/papers/JETIR2407265.pdf

"Statistical Treatment of data for Quantitative Research", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 7, page no. ppc521-c527, July-2024, Available at : http://www.jetir.org/papers/JETIR2407265.pdf