To find the third quartile (Q3) of the scores, you can follow a similar process to that used for finding the first quartile:

1. Determine the position of the third quartile (Q3):

   • The third quartile (Q3) is the 75th percentile of the data.
   • The formula to find the position $P$ of Q3 in an ordered data set is: $P = \frac{3(n+1)}{4}$ where $n$ is the number of data points.

2. Calculate the position:

   • Here, $n = 29$.
   • So, $P = \frac{3(29+1)}{4} = \frac{90}{4} = 22.5$.

3. Interpret the position:

   • Since 22.5 is not an integer, the third quartile will be the average of the 22nd and 23rd data points.

4. Find the 22nd and 23rd data points:

   • The 22nd data point is 88, and the 23rd data point is 90.

5. Calculate Q3: $Q3 = \frac{88 + 90}{2} = \frac{178}{2} = 89$

Thus, the third quartile (Q3) of the scores is 89.

Would you like more details or have any questions? Here are some related questions to expand your understanding:

1. How does the third quartile compare to the mean of this data set?
2. How do you determine if a data set is skewed based on its quartiles?
3. What are the implications of a higher third quartile in a data set?
4. How can you use Q3 to identify outliers in this data set?
5. How would the quartiles change if a new score, say 100, was added to the data set?

Tip: Quartiles are key in identifying the spread and central tendency of data. Q3 is particularly useful in understanding the upper spread of the data set.