Statistical Problem in Analytical Chem

In summary, the conversation discusses a set of chloride concentrations in blood serum and determining if one value can be rejected at a 95% confidence level. The mean and standard deviation were calculated and the t-value was found using a table. The confidence interval was calculated to be 107.5 +/- 7.40. The use of Grubb's test is also mentioned as a possible solution.
  • #1
oxshannon
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0

Homework Statement



The following set of analyses represent concentrations of chloride in blood serum (meq/L): 103,106,107,114. One value appears suspect. Determine if it can be rejected at the 95% confidence level.

Homework Equations


Mean

Standard Deviation:
standard-deviation-2.png


http://www.sjsu.edu/faculty/gerstman/StatPrimer/t-table.pdf"

Degrees of Freedom = n -1 (n in this case being 4)

Confidence Interval:
CI.jpg



The Attempt at a Solution



So I found the mean to 107.5, and the standard deviation to be 4.65 (If anyone wants to see how I did this, just let me know).

Then using the table, I found that t95 = 3.182 (using that there are 3 degrees of freedom)

Using the confidence interval formula, I calculated the answer to be 107.5 +/- 7.40.

I'm stuck from here and in fact have no idea if I even started this problem properly. PLEASE HELP :(
 
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  • #2


Anyone? :( I'm super desperate
 
  • #3


Actually -- would it be possible to simply use Grubb's test?
 
Last edited:

What is "Statistical Problem in Analytical Chem"?

"Statistical Problem in Analytical Chem" refers to the use of statistical methods and techniques in analyzing data and solving problems in the field of analytical chemistry. It involves the application of mathematical models to experimental data in order to draw meaningful conclusions and make accurate predictions.

Why is statistical analysis important in analytical chemistry?

Statistical analysis is important in analytical chemistry because it allows for the evaluation of the reliability and accuracy of experimental data. It helps to identify and correct errors or biases, and to determine the significance of results. This is crucial in ensuring the validity and reproducibility of scientific findings.

What are some common statistical problems encountered in analytical chemistry?

Some common statistical problems in analytical chemistry include data normalization, outlier detection and removal, data transformation, and statistical hypothesis testing. Other challenges may arise from the complex nature of analytical data, such as high dimensionality, non-linearity, and multicollinearity.

How can statistical problems in analytical chemistry be addressed?

Statistical problems in analytical chemistry can be addressed by using appropriate statistical methods and techniques, such as regression analysis, ANOVA, and multivariate analysis. It is important to select the most suitable method based on the type of data and research question. Additionally, ensuring proper experimental design and data quality control can help minimize statistical problems.

What skills and knowledge are required for effective statistical problem solving in analytical chemistry?

To effectively solve statistical problems in analytical chemistry, one needs a strong foundation in statistics, including knowledge of probability distributions, hypothesis testing, and regression analysis. It is also important to have a good understanding of the principles and techniques of analytical chemistry, as well as proficiency in data analysis and interpretation using statistical software.

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