That sounds like the kind of thing you could just Google.
But I’ll bite. Wal-Marts have the advantage of being pretty evenly distributed geographically; there’s rarely more than one within easy driving distance. I recall there being about 15,000 towns in the US, but they aren’t uniformly distributed; they tend to cluster, and even among those that aren’t clustered a good number are going to be too small to support a Wal-Mart. So let’s assume there’s one Wal-Mart per five towns on average, taking into account clustering effects and towns too small or isolated to support one. That gives us a figure of 3,000 Wal-Marts.
When I Google it, that turns out to be irel pybfr gb gur ahzore bs Jny-Zneg Fhcrepragref, gur ynetr syntfuvc fgberf gung gur cuenfr “Jny-Zneg” oevatf gb zvaq. Ubjrire, Jny-Zneg nyfb bcrengrf n fznyyre ahzore bs “qvfpbhag fgber”, “arvtuobeubbq znexrg”, naq “rkcerff” ybpngvbaf gung funer gur fnzr oenaqvat. Vs jr vapyhqr “qvfpbhag” naq “arvtuobeubbq” ybpngvbaf, gur gbgny vf nobhg guerr gubhfnaq rvtug uhaqerq. V pna’g svaq gur ahzore bs “rkcerff” fgberf, ohg gur sbezng jnf perngrq va 2011 fb gurer cebonoyl nera’g gbb znal.
Different method. Assume all 300 million us citizens are served by a Wal Mart. Any population that doesn’t live near a Wal-Mart has to be small enough to ignore. Each Wal-mart probably has between 10,000 and 1 million potential customers. Both fringes seem unlikely, so we can be within a factor of 10 by guessing 100000 people per Wal-Mart. This also leads to 3000 Wal-Marts in the US.
That sounds like the kind of thing you could just Google.
But I’ll bite. Wal-Marts have the advantage of being pretty evenly distributed geographically; there’s rarely more than one within easy driving distance. I recall there being about 15,000 towns in the US, but they aren’t uniformly distributed; they tend to cluster, and even among those that aren’t clustered a good number are going to be too small to support a Wal-Mart. So let’s assume there’s one Wal-Mart per five towns on average, taking into account clustering effects and towns too small or isolated to support one. That gives us a figure of 3,000 Wal-Marts.
When I Google it, that turns out to be irel pybfr gb gur ahzore bs Jny-Zneg Fhcrepragref, gur ynetr syntfuvc fgberf gung gur cuenfr “Jny-Zneg” oevatf gb zvaq. Ubjrire, Jny-Zneg nyfb bcrengrf n fznyyre ahzore bs “qvfpbhag fgber”, “arvtuobeubbq znexrg”, naq “rkcerff” ybpngvbaf gung funer gur fnzr oenaqvat. Vs jr vapyhqr “qvfpbhag” naq “arvtuobeubbq” ybpngvbaf, gur gbgny vf nobhg guerr gubhfnaq rvtug uhaqerq. V pna’g svaq gur ahzore bs “rkcerff” fgberf, ohg gur sbezng jnf perngrq va 2011 fb gurer cebonoyl nera’g gbb znal.
Different method. Assume all 300 million us citizens are served by a Wal Mart. Any population that doesn’t live near a Wal-Mart has to be small enough to ignore. Each Wal-mart probably has between 10,000 and 1 million potential customers. Both fringes seem unlikely, so we can be within a factor of 10 by guessing 100000 people per Wal-Mart. This also leads to 3000 Wal-Marts in the US.