Key Concepts

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Interpretation of Variance

A larger variance means the data is more spread out and values tend to be far away from the mean. A variance of 0 means all values in the dataset are the same.

Variance in R
Lesson 1 of 2
  1. 1
    Finding the mean, median, and mode of a dataset is a good way to start getting an understanding of the general shape of your data However, those three descriptive statistics only tell part of the …
  2. 2
    Now that you have learned the importance of describing the spread of a dataset, let’s figure out how to mathematically compute this number. How would you attempt to capture the spread of the data …
  3. 3
    We now have five different values that describe how far away each point is from the mean. That seems to be a good start in describing the spread of the data. But the whole point of calculating vari…
  4. 4
    We’re almost there! We have one small problem with our equation. Consider this very small dataset: c(-5, 5) The mean of this dataset is 0, so when we find the difference between each point and th…
  5. 5
    Well done! You’ve calculated the variance of a data set. The full equation for the variance is as follows: \sigma^2 = \frac{\sum_{i=1}^{N}{(X_i -\mu)^2}}{N} Let’s dissect this equation a bit. * …
  6. 6
    Great work! In this lesson you’ve learned about variance and how to calculate it. In the example used in this lesson, the importance of variance was highlighted by showing data from test scores in…

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