Most numeric columns are right-skewed or heavy-tailed, and Monthly_Income is the most extreme. Nine columns are numeric. Six of them are stored as text (VARCHAR) and had to be parsed, so each count below is the number of values that parsed, out of 300 rows. The rendered result blocks above show the full figures. **Demographics and income** - **Age** (263 parsed): ranges from 16 to 97, with a mean of 30.2 and a median of 27. The standard deviation is 12.5. The mean sits above the median, so a few older users pull it up, and 97 looks like an outlier. - **Monthly_Income** (284–290 parsed): ranges from 0 to 250,000, with a mean of about 2,304–2,329 and a median of about 520. The standard deviation is about 14,700–14,900, roughly 6 times the mean. A handful of extreme values drive the mean, so the median is the better summary. Because this is a personal-income column, I only report aggregates. **AI usage and cost** - **AI_Usage_Hours_Per_Day** (271 parsed): ranges from 0.5 to 23, with a mean of 3.01 and a median of 2.2. The standard deviation is 2.45. It is right-skewed, and 23 hours a day is implausible and probably a data-entry error. - **Monthly_AI_Cost** (273–288 parsed): ranges from 0 to 100, with a mean of about 9.8 and a median of 0. The standard deviation is about 13.7. Most users pay nothing and a minority pay up to 100. - **Time_Saved_Hours_Per_Week** (272 parsed): ranges from 0 to 19.4, with a mean of 5.81 and a median of 5.05. The standard deviation is 4.11, with mild right skew. - **Work_or_Study_Hours_Per_Day** (279 parsed): ranges from 2.1 to 20, with a mean of 7.29 and a median of 7.2. The standard deviation is 2.14. It is nearly symmetric, though the upper end of 20 hours is questionable. **Ratings and scores** - **Productivity_Score** (284): ranges from 1.6 to 10, with a mean of 5.23 and a median of 5.0. The standard deviation is 1.82, and the distribution is roughly symmetric around the middle. - **Accuracy_Rating** (285): ranges from 2 to 5, with a mean of 3.43 and a median of 4. The standard deviation is 0.86. The median is above the mean, so ratings lean toward the high end with a tail of low ratings. - **Satisfaction_Score** (293): ranges from 3 to 10, with a mean of 6.15 and a median of 6. The standard deviation is 1.52, and the distribution is fairly symmetric. **Data quality** - Between 7 and 37 values per column are missing or could not be parsed. The worst are Age (37 unparsed), AI_Usage_Hours_Per_Day (29) and Time_Saved_Hours_Per_Week (28). - Two of my parsing passes gave different counts for Monthly_Income (290 vs 284) and Monthly_AI_Cost (288 vs 273). The difference comes from how currency-style text was cleaned. The other columns were identical in both passes. I give ranges for those two columns. The mean and median barely change, but the exact count and spread depend on the cleaning rule.