Answer :
Final answer:
To determine if any points can be rejected using Chauvenet's criterion, you must calculate the mean, standard deviation, z-scores, and the probability of occurrence for each data point, then compare the probability to the criterion (1/32 for 16 data points). Any data point with a probability lower than the criterion can be considered an outlier.
Explanation:
To use Chauvenet's criterion for determining if any points can be rejected from the given data set, we will proceed as follows:
- Calculate the mean (average) of the data set.
- Calculate the standard deviation of the data set.
- For each data point, calculate the standardized deviation or z-score, which is the number of standard deviations away from the mean the data point is.
- Using the z-score, determine the probability of a data point occurring (bearing in mind the distribution which is usually considered normal for a large sample size).
- Compare this probability to the Chauvenet's criterion: if the probability is less than (2n)-¹, where n is the number of data points, the data point can be considered an outlier.
For example, if there are 16 data points, the Chauvenet's criterion would reject any data point for which the probability of occurrence is less than 1/32 or 0.03125.
Since the student wants to use Graphpad Prism for analysis, they would input their data into this statistical software to calculate the mean, standard deviation, z-scores and probabilities for each data point, then apply Chauvenet's criterion to identify any potential outliers.
