A researcher conducted a survey on a sample of 2000 college-students in order to examine the relationship between academic achievement and procrastination of studying. Using several indicators and plots of the descriptive statistics, found that in the data were many outlier observations. However, he decided to proceed with the calculation of the correlation coefficient considering the large sample of his research significantly reduces the effect of outliers.

Is this correct? Yes or No.

No, this statement is not correct.

The presence of outliers can affect the calculation of the correlation coefficient and can potentially lead to biased or misleading results. Outliers are extreme values that are significantly different from the rest of the data, and they can have a strong influence on statistical analysis.

When calculating the correlation coefficient, outliers can pull the line of best fit towards them and distort the relationship between the variables. If there are many outlier observations in the data, it is important to address them before calculating the correlation coefficient.

There are various ways to handle outliers, depending on the nature of the data and the research question. One approach is to investigate the outliers more closely to determine if they are legitimate data points or if they are due to data entry errors or other factors. If they are found to be valid data points, their inclusion may still create biased results.

If outliers are determined to be genuine observations but their influence is unwanted or disruptive to the analysis, one can apply statistical techniques such as trimming or winsorizing. Trimming involves removing a percentage of the highest and lowest data values, and winsorizing involves replacing extreme values with less extreme ones.

In summary, it is not accurate to assume that a large sample size will automatically reduce the effect of outliers on the calculation of the correlation coefficient. Handling outliers appropriately is essential to ensure accurate and valid statistical analysis.