"Sample size can affect whether statistically significant differences are found, but sometimes, in extremely large samples, differences are found that are significant but of no real value or interest. What standardized value helps measure the size of the difference in relation to the variability of the data, removing the impact of sample size?"

Effect size

Step-by-step explanation:

Effect size is a simple way of quantifying the difference between two groups that has many advantages over the use of tests of statistical significance alone. Effect size emphasises the size of the difference rather than confounding this with sample size.

we can calculate effect size as

d=\frac{\bar{x}-\mu}{\sigma}

it can measure the effect but here is no need of sample size hence the answer is effect size.

a reflection across the x-axis , followed by the by a reflection across the y-axis , and then a scale dilation of 0.5 .

definitely a. the others have almost all data points on one side of the line.

step-by-step explanation: