Definition: average amount of variability within a data set
2024-11-16
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Definition: average amount of variability within a data set
Population Standard Deviation - Understanding terms \[ \sigma = \text{Standard Deviation} \\ \mu = \text{Population Mean} \\ \bar {x} = \text {Sample Mean} \\ X= \text{Value} \\ N = \text{Total Number of Values of the Population} \\ n = \text{Number of Values in sample} \]
Equation: \[ \sigma= \frac {\sum(X-\mu)^2}{N} \]
Sample Standard Deviation - Understand terms \[ s = \text{Sample Standard Deviation} \\ \bar {x} = \text {Sample Mean} \\ X= \text{Value} \\ n = \text{Number of Values in sample} \]
Equaiton: \[ s = \sqrt{\frac {\sum(X-\bar{x})^2}{n-1}} \]
## Sepal.Length Sepal.Width Petal.Length Petal.Width ## Min. :4.300 Min. :2.300 Min. :1.000 Min. :0.100 ## 1st Qu.:4.800 1st Qu.:3.200 1st Qu.:1.400 1st Qu.:0.200 ## Median :5.000 Median :3.400 Median :1.500 Median :0.200 ## Mean :5.006 Mean :3.428 Mean :1.462 Mean :0.246 ## 3rd Qu.:5.200 3rd Qu.:3.675 3rd Qu.:1.575 3rd Qu.:0.300 ## Max. :5.800 Max. :4.400 Max. :1.900 Max. :0.600 ## Species ## setosa :50 ## versicolor: 0 ## virginica : 0 ## ## ##
## n ## 1 50
## mean.setosadata.Petal.Length. ## 1 1.462
## [1] 0.173664
\[ s = \sqrt{\frac {\sum(X-\bar{x})^2}{n-1}} \\ = \sqrt{\frac {\sum(X-1.462)^2}{50-1}} \\ s = 0.173664 \]