Biology, 26.08.2019 22:10 lex3340

If you were to decide to remove outlying data points from your anaylsis what are two ways you could indicate this in your report to ensure you're being honest about your data analysis

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Answer from: july00

two ways you could indicate this in your report to ensure you're being honest about your data analysis are: Trim the data set, but replace outliers with the nearest “good” data instead of removing.or cutting them off. This is simply refered to as Winsorization. After you have done this, to show you have done this, you can run the data analysis again to confirm if you now have a good result. You can put mean or median especially the one that is in line with your data in place of the outlier so as to replace that variable and to avoid a missing data point.

for better understanding let's explain what an outlier means

An outlier in a data set is simply known as that value among the data that is much higher or much lower than almost all other values. It can change the mean of a data set, but does not affect the median or mode.

from the above we can therefore say that the answer two ways you could indicate this in your report to ensure you're being honest about your data analysis

Trim the data set, but replace outliers with the nearest “good” data instead of removing.or cutting them off. This is simply refered to as Winsorization. After you have done this, to show you have done this, you can run the data analysis again to confirm if you now have a good result. You can put mean or median especially the one that is in line with your data in place of the outlier so as to replace that variable and to avoid a missing data point, is correct

learn more about outlier from:

link

Answer from: kingindoraptor

Explanation:

If the outlying data points are to be removed from the report to ensure the data analysis is correct is to remove it only if that is wrong or if I have a lot of data or if we can go back and verify the data points again.

We shouldn’t remove it if the results are critical and there are many outlying data points. While removing the data points, we can trim the data set or replace the outlying data points with nearest data or we can also replace the outliers with mean or median.

Answer from: Quest

the genotypes would be 50% bb and 50% bb

the phenotypes would be 50% brown and 50% white. hope this : )

Answer from: Quest

answer; i believe the correct answer is (replication is not conservative);

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