**The data is mostly clean, with a few things to watch.** The checks found no impossible values, no mixed units and no format problems. The real issues are some missing values, some pile-ups at the scale limits, and one implausible age/level combination. **What looks fine** - **IDs:** All 4,500 `Student_ID` values are distinct and non-null, and every ID is 11 characters long (`STU_2024000` to `STU_2028499`). One of my format checks flagged all 4,500 rows as "odd", but that is inconsistent with the length and range results. I treat it as a faulty pattern in my check, not a real problem. - **Ranges:** Every numeric column sits inside a plausible range: - Age 15–26 - Daily usage 0.9–14.0 hours - Weekend extra hours 0–4.5 - Sleep 3.0–10.5 hours - Sleep quality 1–5 - Mental health index 32–98 - Stress 0–40 - GPA 1.9–4.0 - **Units:** Nothing suggests mixed units. No usage figures look like minutes, and no GPAs are on a 0–100 scale. - **Time budget:** No row has daily usage plus sleep above 20 hours, so no one has an impossible day. - **Categories:** Every categorical column has no nulls and no variant spellings. Gender, level, platform, device, comparison frequency, impact and late-night flag all show clean label sets. **Issues worth flagging** 1. **Missing values.** GPA is null in 85 rows (1.9%) and `Perceived_Stress_Score` is null in 46 rows (1.0%). Every other measure has zero nulls. Averages and correlations on these two columns will use fewer than 4,500 students. 2. **GPA ceiling.** 353 rows (about 8% of the 4,415 non-null GPAs) sit exactly at 4.0. This looks like capping or clipping, so the top of the GPA distribution is compressed. It will understate any relationship between GPA and the other measures. 3. **Age versus academic level.** 156 of the 1,477 High School students (about 10.6%) are aged 19 or older. That is unusual for high school and may be a labelling error or a different population. By contrast, no postgraduates are aged 20 or under and no undergraduates are 16 or under. 4. **Stress at the extremes.** 87 students have a stress score of exactly 0 and 8 have exactly 40, the scale's limits. A score of 0 is rarely realistic, so some may be placeholders or defaults. 5. **Pile-ups at the edges of other scales.** - 55 students are at the 14.0-hour daily usage maximum. - 11 are at the 3.0-hour sleep floor and 1 is at the 10.5-hour sleep cap. - 126 students report 12 or more hours of use a day. The usage and sleep figures are consistent with each other, but these look like capped or self-reported values and should not be read as precise. 6. **Imbalanced groups.** Overall impact is 3,681 Beneficial, 654 Neutral and only 165 Negative. Postgraduates (246), Tablet users (129), LinkedIn (96) and "Prefer not to say" gender (93) are small groups. Their averages will be noisy. I did not check the ingestion metadata columns (`_batch_id`, `_source_file`, `_source_system`, `_ingestion_timestamp`). **Suggested handling:** Treat the null GPA and stress rows as missing rather than filling them in. Treat the GPA 4.0 cap as a ceiling effect. Review the older "High School" students, and treat stress scores of exactly 0 with caution.