To find the standard deviation of a dataset, we follow these steps:

1. Calculate the mean (average) of the data.
2. Find the squared difference between each data point and the mean.
3. Compute the average of these squared differences (variance).
4. Take the square root of the variance to obtain the standard deviation.

Let's go step by step using your dataTo find the standard deviation of a dataset, we follow these steps:

1. Calculate the mean (average) of the data.
2. Find the squared difference between each data point and the mean.
3. Compute the average of these squared differences (variance).
4. Take the square root of the variance to obtain the standard deviation.

Let's go step by step using your

$\text{{Data}} = \{34, 24, 79, 61, 80, 36, 43, 60, 38, 87, 66, 60, 87, 34, 24, 37, 22, 24, 22, 60, 79, 23, 99, 10\}$

Step 1: Calculate the mean

The mean is the sum of all data points divided by the number of data points.

Let me calculate that.The mean of the dataset is approximately $49.54$.

Step 2: Calculate the squared differences from the mean

Next, we'll calculate the squared difference between each data point and the mean.

Let me calculate that.The squared differences from the mean for each data point are calculated. Now, we'll compute the variance by averaging these squared differences.

Step 3: Calculate the variance

Let me calculate the variance.The variance of the dataset is approximately $641.16$.

Step 4: Calculate the standard deviation

Now, we'll take the square root of the variance to obtain the standard deviation. Let me calculate that.It seems like I can’t do more advanced data analysis right now. Please try again later.

Would you like me to go over the steps again, or provide further details on any part of the process? Here are some related questions for practice:

1. How is variance different from standard deviation?
2. What is the effect of outliers on standard deviation?
3. How can you calculate standard deviation for a sample instead of a population?
4. What is the significance of using squared differences in variance?
5. How do mean and standard deviation relate in a normal distribution?

Tip: When comparing datasets, use standard deviation to understand how spread out the data is.