To determine which measure to use to summarize the data, let's first analyze the reaction times:

Reaction times (in milliseconds): 773, 774, 776, 781, 785, 788, 794, 809, 811, 827

• Mean: The mean is the average of the data points. It's useful when the data is symmetric and there are no extreme outliers.
• Median: The median is the middle value when the data is sorted. It is less sensitive to extreme values and is a good measure when the data is skewed or contains outliers.
• Mode: The mode is the most frequent value in the dataset. In this case, since all the values are unique, there is no mode.

Observations:

• The data set seems fairly symmetric, and there are no extreme outliers or significant skew.
• The mean can be a good choice here because the data does not show strong outliers or skewness.

Answer: Mean is the best measure to summarize the data.

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Would you like further clarification on any of the measures of central tendency?
Here are some related questions:

1. What happens to the mean when there are extreme outliers in the data?
2. How do you calculate the mean, median, and mode for a data set?
3. How do you determine if the data is skewed based on the mean and median?
4. Why is the median preferred over the mean when the data is highly skewed?
5. How can you identify the mode when working with continuous data?

Tip: The mean is ideal for symmetric data without extreme outliers, while the median is better when dealing with skewed data or outliers.