You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 student_club
【Schema】
# Table: major
[
(major_id:TEXT, Primary Key, Examples: [rec06DF6vZ1CyPKpc, rec09LedkREyskCNv, rec0Eanv576RhQllI]),
(major_name:TEXT, Examples: [Outdoor Product Design and Development]),
(department:TEXT),
(college:TEXT, Examples: [College of Agriculture and Applied Sciences])
]
# Table: budget
[
(budget_id:TEXT, Primary Key, Examples: [rec0QmEc3cSQFQ6V2, rec1bG6HSft7XIvTP, rec1z6ISJU2HdIsVm]),
(category:TEXT, Examples: [Advertisement, Food, Speaker Gifts]),
(spent:REAL, Examples: [67.81, 121.14, 20.2]),
(remaining:REAL, Examples: [7.19, 28.86, -0.199999999999999]),
(amount:INTEGER, Examples: [75, 150, 20]),
(event_status:TEXT, Examples: [Closed, Open, Planning]),
(link_to_event:TEXT, Examples: [recI43CzsZ0Q625ma, recggMW2eyCYceNcy, recJ4Witp9tpjaugn])
]
# Table: member
[
(member_id:TEXT, Primary Key, Examples: [rec1x5zBFIqoOuPW8, rec280Sk7o31iG0Tx, rec28ORZgcm1dtqBZ]),
(first_name:TEXT, Examples: [Angela, Grant, Luisa]),
(last_name:TEXT, Examples: [Sanders, Gilmour, Guidi]),
(email:TEXT),
(position:TEXT, Examples: [Member, Inactive, President]),
(t_shirt_size:TEXT, Examples: [Medium, X-Large, Large]),
(phone:TEXT, Examples: [(651) 928-4507, 403-555-1310, 442-555-5882]),
(zip:INTEGER, Examples: [55108, 29440, 10002]),
(link_to_major:TEXT, Examples: [recxK3MHQFbR9J5uO, rec7BxKpjJ7bNph3O, recdIBgeU38UbV2sy])
]
# Table: zip_code
[
(zip_code:INTEGER, Primary Key, Examples: [501, 544, 601]),
(type:TEXT, Examples: [Unique, Standard, PO Box]),
(city:TEXT, Examples: [Holtsville, Adjuntas, Aguada]),
(county:TEXT, Examples: [Suffolk County, Adjuntas Municipio, Aguada Municipio]),
(state:TEXT, Examples: [New York, Puerto Rico, Massachusetts]),
(short_state:TEXT, Examples: [NY, PR, MA])
]
# Table: income
[
(income_id:TEXT, Primary Key, Examples: [rec0s9ZrO15zhzUeE, rec7f5XMQZexgtQJo, rec8BUJa8GXUjiglg]),
(date_received:TEXT, Examples: [2019-10-17, 2019-09-04, 2019-10-08]),
(amount:INTEGER, Examples: [50, 200, 3000]),
(source:TEXT, Examples: [Dues, Fundraising, School Appropration]),
(notes:TEXT),
(link_to_member:TEXT, Examples: [reccW7q1KkhSKZsea, recTjHY5xXhvkCdVT, recUdRhbhcEO1Hk5r])
]
# Table: attendance
[
(link_to_event:TEXT, Primary Key, Examples: [rec2N69DMcrqN9PJC, rec5XDvJLyxDsGZWc, recEVTik3MlqbvLFi]),
(link_to_member:TEXT, Primary Key, Examples: [recD078PnS3x2doBe, recP6DJPyi5donvXL, rec28ORZgcm1dtqBZ])
]
# Table: expense
[
(expense_id:TEXT, Primary Key, Examples: [rec017x6R3hQqkLAo, rec1nIjoZKTYayqZ6, rec1oMgNFt7Y0G40x]),
(expense_description:TEXT, Examples: [Post Cards, Posters, Water, Cookies, Pizza]),
(expense_date:TEXT, Examples: [2019-08-20, 2019-10-08, 2019-09-10]),
(cost:REAL, Examples: [122.06, 20.2, 51.81]),
(approved:TEXT, Examples: [true]),
(link_to_member:TEXT, Examples: [rec4BLdZHS2Blfp4v, recro8T1MPMwRadVH, recD078PnS3x2doBe]),
(link_to_budget:TEXT, Examples: [recvKTAWAFKkVNnXQ, recy8KY5bUdzF81vv, recwXIiKoBMjXJsGZ])
]
# Table: event
[
(event_id:TEXT, Primary Key, Examples: [rec0Si5cQ4rJRVzd6, rec0akZnLLpGUloLH, rec0dZPcWXF0QjNnE]),
(event_name:TEXT, Examples: [March Meeting]),
(event_date:TEXT, Examples: [2020-03-10T12:00:00, 2020-01-14T09:30:00, 2019-11-24T09:00:00]),
(type:TEXT, Examples: [Meeting, Election, Game]),
(notes:TEXT),
(location:TEXT, Examples: [MU 215]),
(status:TEXT, Examples: [Open, Planning, Closed])
]
【Foreign keys】
budget.link_to_event=event.event_id
member.link_to_major=major.major_id
member.zip=zip_code.zip_code
income.link_to_member=member.member_id
attendance.link_to_event=event.event_id
attendance.link_to_member=member.member_id
expense.link_to_budget=budget.budget_id
expense.link_to_member=member.member_id

    【Question】
    List the expenses that spend more than fifty dollars on average. expense refers to expense_description; spend more than fifty dollars on average refers to DIVIDE( SUM(cost), COUNT(expense_id) ) > 50

    【Evidence】
    expense refers to expense_description; spend more than fifty dollars on average refers to DIVIDE( SUM(cost), COUNT(expense_id) ) > 50

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT expense_description FROM expense GROUP BY expense_description HAVING AVG(cost) > 50