Negative values for Gaussian Distribution

In summary, the conversation discussed a Physics lab where the class threw darts at a target with 13 bins. The class then combined their average, standard deviation, and standard error. The speaker created a Gaussian Distribution and noticed a negative value for the third standard deviation below the mean. The target was just a paper pinned to the wall and the negative value represents the probability of someone being bad at aiming and landing to the left of the first bin.
  • #1
aron silvester
So in my Physics lab, we divided into groups and our task was to throw darts on a target containing 13 bins. The bins look something like the image below. At the end, our class combined our average, standard deviation, and standard error. I made a Gaussian Distribution and I noticed that the third standard deviation below the mean of 7.22 is equal to -0.88. Is this possible to have a negative value even though there were only 13 bins?

Class Data:
Average: 7.22
Standard Deviation: 2.7
Standard Error: 0.085

Here is the target. It was just a paper that we pinned to the wall.
IMG_1594.JPG


Here is the Gaussian Distribution that I created with the negative value.
IMG_1595.JPG
 
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  • #2
Since you have labelled the bins left to right in order, the number can be thought to measure distance from the origin where the origin is one box to the left of box 1. There is nothing wrong with the distribution. Its telling you that there is some finite probability that someone is really bad at aiming and throws a dart which lands to the left of box 1.
 

FAQ: Negative values for Gaussian Distribution

1. What are negative values in a Gaussian Distribution?

Negative values in a Gaussian Distribution refer to data points that fall below the mean of the distribution. In a Gaussian or normal distribution, the mean is considered the central tendency of the data and the majority of data points fall within one standard deviation of the mean. Negative values are important to consider when analyzing data, as they can affect the overall shape and interpretation of the distribution.

2. Can a Gaussian Distribution have negative values?

Yes, a Gaussian Distribution can have negative values. In fact, it is common for some data points to fall below the mean in a normal distribution. However, the majority of data points will fall within one standard deviation of the mean, with a smaller proportion of data points falling in the negative range.

3. What do negative values indicate in a Gaussian Distribution?

Negative values in a Gaussian Distribution indicate that the data points are below the mean or central tendency of the data. This could suggest that there are outliers or extreme values in the dataset, or that the data is skewed to the left. It is important to investigate the reasons for negative values and consider their impact on the overall distribution.

4. How do negative values affect the shape of a Gaussian Distribution?

Negative values can affect the shape of a Gaussian Distribution by pulling the mean to the left and potentially creating a skewed distribution. This can change the overall shape of the distribution and make it asymmetrical. In some cases, negative values may also increase the kurtosis or "peakedness" of the distribution.

5. How do you handle negative values in a Gaussian Distribution?

The handling of negative values in a Gaussian Distribution depends on the specific dataset and the goals of the analysis. In some cases, it may be appropriate to remove or transform the negative values. In other cases, it may be important to keep the negative values and investigate their potential impact on the overall distribution. It is important to carefully consider the reasons for negative values and their potential impact before making any decisions on how to handle them.

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