Final answer:
The power of the study can be estimated using statistical software based on the provided sample sizes, desired detectable difference, standard deviation, and significance level. Simulating power with 10,000 iterations as mentioned in the question is impractical without software, but the concept involves using these parameters to determine the likelihood of detecting the specified effect size.
Step-by-step explanation:
The question involves the concept of statistical power, which is used in hypothesis testing to determine the ability of a study to detect a difference, if a difference truly exists. To estimate the power of the study with 75 raccoons in the treatment group and 100 in the control group, we need to consider the desired detectable difference of 1 unit, the standard deviation of 2.5, and the level of significance of 0.05. However, the actual calculation of power typically would use a statistical software or a specific power analysis formula, rather than a simulation with 10,000 iterations which is mentioned in the question. Nonetheless, the concept can be explained.
To calculate the power, one would typically use the standard deviation, sample sizes of both groups, the significance level, and the effect size (the detectable difference divided by the standard deviation). By knowing the sample size, significance level, and standard deviation, you would calculate the effect size, which is 1/2.5 = 0.4 in this case, and then use a power analysis calculator or software to determine the power.
A general rule in statistics is that larger sample sizes and smaller standard deviations increase the power of the study, which means the study is more likely to detect the specified effect size.