Characterizing Top 5% of Influent Substrate Concentration in Reactor

In summary, Normal Standardization is a statistical method used to transform data into a standard normal distribution, making it easier to compare and analyze. It is important because it allows for easier comparison across variables and datasets and can identify outliers and trends. It is calculated by subtracting the mean from each data point and dividing by the standard deviation. Benefits include interpretability and easier analysis, but it may not be appropriate for all datasets and can still be impacted by extreme outliers. It is important to consider the nature of the data and purpose of analysis when using Normal Standardization.
  • #1
needhelp83
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0
Substrate concentration (mg/cm^3) of influent to a reactor is normally distributed with [tex]\mu = 0.30[/tex] and [tex]\sigma[/tex] = .06

The question is how would you characterize the largest 5% of all concentration values?

What does this mean?
 
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  • #2
I think its probably P(X>=k) = 0.05, solve for k.
 
  • #3
Fightfish said:
I think its probably P(X>=k) = 0.05, solve for k.

P(X >= k) =0.05
1- n = 0.05 n= 0.95 (Look up value in z-table)
1.64 = 0.9495

[tex]\frac{k - 0.30}{0.06}=0.9495[/tex]

After solving, k = 0.36
 

Related to Characterizing Top 5% of Influent Substrate Concentration in Reactor

What is Normal Standardization?

Normal Standardization is a statistical method used to transform a set of data into a standard normal distribution, also known as a bell curve. This allows for easier comparison and analysis of data.

Why is Normal Standardization important?

Normal Standardization is important because it allows for easier comparison of data across different variables and datasets. It also makes data more interpretable and can help identify outliers and trends within the data.

How is Normal Standardization calculated?

Normal Standardization is calculated by subtracting the mean from each data point and then dividing by the standard deviation. This transforms the data into a standard normal distribution with a mean of 0 and a standard deviation of 1.

What are the benefits of using Normal Standardization?

Using Normal Standardization can provide several benefits, including making data more interpretable, allowing for easier comparison and analysis, and identifying outliers and trends within the data.

Are there any limitations to Normal Standardization?

While Normal Standardization can be a useful tool, it is not always appropriate for all datasets. It assumes a normal distribution of the data, which may not always be the case. Additionally, extreme outliers can still impact the standardized data. It is important to consider the nature of the data and the purpose of the analysis before using Normal Standardization.

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