The mean and standard deviation are two fundamental concepts in statistics that describe data sets. The mean provides a measure of central tendency, indicating the average value in a data distribution. In our context, we calculate the mean length of lizards as follows:
\( \text{Mean} = \frac{\sum \text{(length * number of lizards)}}{\text{sample size}} \)
For the lizard lengths:
\( \text{Mean} = \frac{700}{100} = 7 \text{ cm} \)
On the other hand, standard deviation describes how spread out the values are around the mean. A small standard deviation signifies that the data points are close to the mean, while a large one indicates more variability.
Let's compute it for our lizards:
\( \text{Standard Deviation} = \sqrt{\frac{\sum (\text{length}_i - \text{mean})^2 \times \text{number of lizards}}{\text{sample size}}} \)
This comes out to approximately 1.11 cm in our example.
- Use the mean to summarize your data and understand its general trend.
- Rely on standard deviation to gauge data variability and predictability.