The interview report preserved the survey tables and the request to compare response levels for new and old users, but it explicitly noted that the interviewer should clarify the cohort definition. The following is a self-contained practice reconstruction with that business rule supplied. You have two PostgreSQL tables: ```text survey ------ user_id BIGINT NOT NULL event_date DATE NOT NULL survey_event TEXT NOT NULL -- 'impression' or 'response' response INTEGER NULL -- 1 through 5 for a response; NULL for an impression users ----- user_id BIGINT PRIMARY KEY reg_date DATE NOT NULL country TEXT NOT NULL ``` Every `survey.user_id` has a matching `users` row. For this exercise: - A response from day 0 through day 29 after registration is from a `new` user. - A response on day 30 or later is from an `established` user. - Rows dated before `reg_date` are invalid and must be excluded. - Only rows with `survey_event = 'response'` and a non-null integer `response` from 1 through 5 are included. - Each qualifying row is one response event; a user may respond on multiple dates and each event counts. Write one PostgreSQL query that returns, for each `country` and user cohort: - `country` - `user_cohort`: exactly `new` or `established` - `response_events`: number of qualifying response events - `responding_users`: number of distinct users with at least one qualifying response in the cohort - `average_response`: the arithmetic mean of the qualifying 1-to-5 responses as a numeric value Do not emit groups with zero qualifying responses. Preserve numeric precision and order by `country` ascending, then `user_cohort` ascending.