This page assumes you have seen none of the notation on the parent note. We build every symbol, one at a time, each resting on the previous. If you can count and share sweets among friends, you can follow every line.
Before any symbol, hold this image: a row of buckets (think laundry baskets in a corridor), and a pile of keys (think named socks) that must each be dropped into exactly one basket by a rule.
Everything below is a label for something in this picture.
If you insert one more key, n goes up by one. If you delete one, n goes down by one. Nothing subtle — but every later formula uses this letter, so we name it first.
We have a count of stuff (n) and a count of space (m). The natural question "how crowded?" is answered by dividing one by the other.
Why the topic needs α: it is the single dial the whole page turns. Small α = fast + wasteful; large α = cramped + slow. Resizing is nothing but keeping this one number in a safe range.
Cover the right side; say your answer aloud before revealing.
n means
the number of keys currently stored in the table.
m means
the number of buckets (slots), full or empty.
α=n/m is
the load factor — average items per bucket / how crowded the table is.
Why divide n by m instead of subtracting?
crowdedness is a ratio; division gives the same answer for proportionally-scaled tables.
h(k) is
the hash function — a rule turning a key into a fixed number.
amodm means
the remainder of a divided by m; it wraps any number into 0…m−1.
Why can't you copy buckets on resize?
the bucket is h(k)modm; changing m changes the remainder, so keys must be re-placed.
A collision is
two different keys sent to the same bucket.
O(1) versus O(n)
constant work (doesn't grow) versus linear work (grows in proportion to size).
E[X] means
the average outcome over many repetitions.
The geometric series 1+r+r2+⋯ for 0≤r<1 sums to
1−r1.
∑i=1k means
add the term for i=1,2,…,k.
Amortized cost is
average cost per operation over a run where rare operations are expensive.
Ready? Then head back to the parent topic (or its English version) and every symbol will already be an old friend. See also Hashing and Dynamic Arrays for where doubling first appears.