drop table Region 
go 
drop table Sales 
go 

create table Region(id int, name nvarchar(100)) 
go 
create table Sales(id int, detail int) 
go 
create clustered index d1 on Region(id) 
go 
create index ix_Region_name on Region(name) 
go 
create statistics ix_Region_id_name on Region(id, name) 
go 
create clustered index ix_Sales_id_detail on Sales(id, detail) 
go 

-- only two values in this table as lookup or dim table 
insert Region values(0, 'Dallas') 
insert Region values(1, 'New York') 
go 

set nocount on 
-- Sales is skewed 
insert Sales values(0, 0) 
declare @i int 
set @i = 1 
while @i <= 1000 begin 
insert Sales  values (1, @i) 
set @i = @i + 1 
end 
go 

update statistics Region with fullscan 
update statistics Sales with fullscan 
go 

set statistics profile on 
go 
--note that this query will over estimate 
-- it estimate there will be 500.5 rows 
select detail from Region join Sales on Region.id = Sales.id where name='Dallas' option (recompile) 
--this query will under estimate 
-- this query will also estimate 500.5 rows in fact 1000 rows returned 
select detail from Region join Sales on Region.id = Sales.id where name='New York' option (recompile) 
go 

set statistics profile off 
go 

create statistics Region_stats_id on Region (id) 
where name = 'Dallas' 
go 
create statistics  Region_stats_id2 on Region (id) 
where name = 'New York' 
go 

set statistics profile on 
go 
--now the estimate becomes accurate (1 row) because 
select detail from Region join Sales on Region.id = Sales.id where name='Dallas' option (recompile) 

--the estimate becomes accurate (1000 rows) because stats Region_stats_id2 is used to evaluate 
select detail from Region join Sales on Region.id = Sales.id where name='New York' option (recompile) 
go 

set statistics profile off