Final answer:
Removing the outlier 35 from the data set will decrease the mean, providing a more accurate representation of the data set's central tendency without the skewing effect of the outlier.
Step-by-step explanation:
The question poses a scenario where there is a data set containing the numbers: 10, 10, 11, 12, 13, 13, 13, 14, 14, 15, 15, 15, 16, 17, 17, 17, 35. We are asked about the effect of removing the outlier, 35, on the mean of the data set. An outlier is a number in a data set that is significantly higher or lower than the other numbers. Outliers can skew the data, affecting measures of central tendency like the mean.
Calculating the mean with the outlier 35 included gives us a mean (average) higher than the median and mode, which indicates a right-skewed distribution because the outlier pulls the mean upwards. Removing the outlier will result in a lower mean since the sum of the remaining numbers will be divided by the same count but without the high value of 35. Therefore, the mean of the data set will decrease if we remove the outlier 35, and we will have a mean that better represents the central tendency without the induced variability caused by the outlier.