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Unit 1: StatisticsDate:Day 4: Standard Deviation vs. IQR#4 Example: Calculating the Standard Deviation A consumers organization is planning a study of the various brands of batteries that are available.
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01
Calculate the mean of the data set.
02
Find the difference between each data point and the mean.
03
Square each difference and sum up all the squared differences.
04
Divide the sum of squared differences by the number of data points minus one to get the variance.
05
Take the square root of the variance to get the standard deviation.
06
Arrange the data set in ascending order.
07
Find the first quartile (Q1) and the third quartile (Q3).
08
Calculate the interquartile range (IQR) by subtracting Q1 from Q3.

Who needs standard deviation vs iqr?

01
Researchers and statisticians who want to measure the spread or dispersion of a data set may use both standard deviation and Interquartile Range (IQR).
02
Standard deviation is often preferred when the data is normally distributed and outliers are present, while IQR is robust in handling outliers and skewed data.
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Standard deviation measures the dispersion of data points from the mean, indicating how spread out the values are in a dataset. The interquartile range (IQR) measures the range of the middle 50% of the data, which helps to identify the spread of the central part of the dataset.
Individuals and organizations that are involved in statistical reporting or analysis may be required to report standard deviation and IQR, particularly in fields like finance, research, and data analysis.
To fill out standard deviation, calculate the mean of the dataset, then find the variance by averaging the squared differences from the mean, and finally take the square root of the variance. For IQR, sort the data, find the first quartile (Q1) and the third quartile (Q3), and subtract Q1 from Q3.
The purpose of standard deviation is to understand the variability of a dataset, while IQR is used to identify the spread of the middle 50% of the data, reducing the influence of outliers.
Reports should include the calculated standard deviation, IQR, the dataset used, and any relevant context or interpretations of these statistics.
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