Methods to describe a data set

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In summary, the conversation is discussing the most accurate method of describing a data set of voltage vs time for a cycle, where voltage varies due to thermal effects. The speaker is trying to find a single thrust measurement number for the entire cycle, but taking the average of the instantaneous thrust measurements may not accurately represent the data due to thermal drift. They are seeking advice on other methods or obtaining more data for a more accurate description.
  • #1
antz0r
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Hello,

This might be a simple question but I am trying to find a good method of describing a data set. I have a data set of voltage vs time for a cycle, where voltage varies a lot. Would taking the average of voltage over the entire number of times be a good way of describing everything? Or are there other more accurate methods of getting a single and accurate voltage number for the whole cycle?

Thanks
 
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  • #2
Would tell about this more precisely:
where voltage varies a lot.
?
 
  • #3
The voltage indicates the thrust measurement at that time. So if I convert it to thrust, it would be around 50mlbf most of the times. However, because of thermal effects (ie the instruments heat up), the measurements slowly increase over time and decrease once the device is turned off. The problem is that I don't know the exact amount it drifts because there's really no way to measure it.

I'm trying to get a single thrust measurement number for one run cycle that can describe the data. Due to the thermal drift, it's hard to represent the measurement if I just take the average of all the instantaneous thrust measurements over time. Are there any other methods of describing the data set as accurately as possible?
 
  • #4
antz0r said:
The voltage indicates the thrust measurement at that time. So if I convert it to thrust, it would be around 50mlbf most of the times. However, because of thermal effects (ie the instruments heat up), the measurements slowly increase over time and decrease once the device is turned off. The problem is that I don't know the exact amount it drifts because there's really no way to measure it.

I'm trying to get a single thrust measurement number for one run cycle that can describe the data. Due to the thermal drift, it's hard to represent the measurement if I just take the average of all the instantaneous thrust measurements over time. Are there any other methods of describing the data set as accurately as possible?

You seem to need MORE data. One single measurement will not give you much to use for graphing or other numeric processing. An engineer-person should probably give you well directed advice. Do you maybe have some way to create a model to predict what value should be found in measurement?
 
  • #5
for your question! There are several methods that can be used to describe a data set, and the best approach will depend on the specific characteristics and goals of your data analysis. In the case of your voltage vs time data set, taking the average of voltage over the entire cycle may provide a general overview of the data. However, it may not accurately capture any variations or patterns within the cycle. Other methods that you could consider include calculating the median or mode of the data, which may provide a better representation of the central tendency of the data. Additionally, you could also plot the data and visually analyze any trends or patterns. Depending on the purpose of your analysis, you may also want to consider calculating measures of variability, such as standard deviation or range, to better understand the spread of the data. Ultimately, the best method for describing your data set will depend on your specific research question and the characteristics of your data.
 

1. What are the different types of methods used to describe a data set?

The most commonly used methods to describe a data set are measures of central tendency (mean, median, and mode), measures of variability (range, variance, and standard deviation), and measures of relative position (percentiles and quartiles).

2. How do measures of central tendency describe a data set?

Measures of central tendency provide a single value that represents the typical or average value of a data set. The mean is the sum of all values divided by the number of values, the median is the middle value when the data set is arranged in order, and the mode is the most frequently occurring value.

3. What do measures of variability indicate about a data set?

Measures of variability describe the spread or dispersion of the data set. The range is the difference between the highest and lowest values, the variance is the average of the squared differences from the mean, and the standard deviation is the square root of the variance.

4. How does the use of percentiles and quartiles describe a data set?

Percentiles and quartiles are measures of relative position that divide a data set into equal parts. The median is the 50th percentile, the first quartile is the 25th percentile, and the third quartile is the 75th percentile. They provide information about the distribution of values in a data set.

5. When should I use graphical methods to describe a data set?

Graphical methods are useful for visualizing the data and identifying patterns or trends. They are particularly helpful when the data set is large or complex, as they can provide a quick and easy way to summarize the data and communicate the findings to others. Graphs can also be used to compare multiple data sets.

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