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

    【Schema】
    【DB_ID】 regional_sales
【Schema】
# Table: Customers
[
(CustomerID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Customer Names:TEXT, Examples: [Avon Corp, WakeFern , Elorac, Corp])
]
# Table: Sales Team
[
(SalesTeamID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Sales Team:TEXT, Examples: [Adam Hernandez, Keith Griffin, Jerry Green]),
(Region:TEXT, Examples: [Northeast, West, South])
]
# Table: Sales Orders
[
(OrderNumber:TEXT, Primary Key, Examples: [SO - 0001000, SO - 0001001, SO - 0001002]),
(Sales Channel:TEXT, Examples: [In-Store, Online, Distributor]),
(WarehouseCode:TEXT, Examples: [WARE-UHY1004, WARE-NMK1003, WARE-PUJ1005]),
(ProcuredDate:TEXT, Examples: [12/31/17, 4/10/18, 7/19/18]),
(OrderDate:TEXT, Examples: [5/31/18, 6/1/18, 6/2/18]),
(ShipDate:TEXT, Examples: [6/14/18, 6/22/18, 6/21/18]),
(DeliveryDate:TEXT, Examples: [6/19/18, 7/2/18, 7/1/18]),
(CurrencyCode:TEXT, Examples: [USD]),
(_SalesTeamID:INTEGER, Examples: [6, 14, 21]),
(_CustomerID:INTEGER, Examples: [15, 20, 16]),
(_StoreID:INTEGER, Examples: [259, 196, 213]),
(_ProductID:INTEGER, Examples: [12, 27, 16]),
(Order Quantity:INTEGER, Examples: [5, 3, 1]),
(Discount Applied:REAL, Examples: [0.075, 0.05, 0.1]),
(Unit Price:TEXT, Examples: [1,963.10, 3,939.60, 1,775.50]),
(Unit Cost:TEXT, Examples: [1,001.18, 3,348.66, 781.22])
]
# Table: Products
[
(ProductID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Product Name:TEXT, Examples: [Cookware, Photo Frames, Table Lamps])
]
# Table: Regions
[
(StateCode:TEXT, Primary Key, Examples: [AL, AR, AZ]),
(State:TEXT, Examples: [Alabama, Arkansas, Arizona]),
(Region:TEXT, Examples: [South, West, Northeast])
]
# Table: Store Locations
[
(StoreID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(City Name:TEXT, Examples: [Birmingham, Huntsville, Mobile]),
(County:TEXT, Examples: [Shelby County/Jefferson County]),
(StateCode:TEXT, Examples: [AL, AR, AZ]),
(State:TEXT, Examples: [Alabama, Arkansas, Arizona]),
(Type:TEXT, Examples: [City, Town, CDP]),
(Latitude:REAL, Examples: [33.52744, 34.69901, 30.69436]),
(Longitude:REAL, Examples: [-86.79905, -86.67298, -88.04305]),
(AreaCode:INTEGER, Examples: [205, 256, 251]),
(Population:INTEGER, Examples: [212461, 190582, 194288]),
(Household Income:INTEGER, Examples: [89972, 78554, 76170]),
(Median Income:INTEGER, Examples: [31061, 48775, 38776]),
(Land Area:INTEGER, Examples: [378353942, 552604579, 361044263]),
(Water Area:INTEGER, Examples: [6591013, 3452021, 105325210]),
(Time Zone:TEXT, Examples: [America/Chicago, America/Phoenix, America/Los Angeles])
]
【Foreign keys】
Sales Orders._ProductID=Products.ProductID
Sales Orders._StoreID=Store Locations.StoreID
Sales Orders._CustomerID=Customers.CustomerID
Sales Orders._SalesTeamID=Sales Team.SalesTeamID
Store Locations.StateCode=Regions.StateCode

    【Question】
    In which region can you find the stores located in the state whose median income is no more than 30,000? median income no more than 30,000 refers to Median Income < 30,000

    【Evidence】
    median income no more than 30,000 refers to Median Income < 30,000

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

SQL: SELECT T FROM ( SELECT DISTINCT CASE  WHEN T2.`Median Income` < 30000 THEN T1.Region END AS T FROM Regions T1 INNER JOIN `Store Locations` T2 ON T2.StateCode = T1.StateCode ) WHERE T IS NOT NULL