Before proceeding you might wish to read, in less technical terms, what constitutes a statistical tie.
A sample must be is randomly drawn from a population. To use this (approximate) method we must assume that the sample size is less than 10% of the size of the population. In addition, at least 10 polled voters must indicate a preference for each of the candidates being assessed.
For an example, suppose we randomly select 1359 likely registered voters about the 2000 election, asking "Which of the following candidates do you prefer for President?" At the time of the polling (it is currently February of 2000) there are still a number of candidates. Here are the poll results:
Candidate  # Favoring  % Favoring 

Al Gore  315  23.18 
George W. Bush  287  21.12 
Bill Bradley  203  14.94 
John McCain  185  13.61 
Steve Forbes  113  8.31 
Alan Keyes  65  4.78 
Gary Bauer  27  1.99 
Other  38  2.80 
Undecided  126  9.27 
Let P_{A} and P_{B} be the true (population) results for candidates A and B. Determining a statistical tie is equivalent to testing
H_{0}: P_{A}  P_{B} = 0 H_{A}: P_{A } P_{B} ¹ 0 .
The poll result is designated a statistical tie if the decision is to not reject H_{0} at the given significance level a. Almost always, for media polls, a = 5%.
The appropriate test statistic is given by
or 
The first expression  based on the estimated proportions (the "hatted values") is preferred conceptually because it puts the quantity in the standard form of
Estimate of difference: 

divided by the 

Standard Error of the estimate: 
where the standard error shrinks as the sample size grows. The other expression, using the observed counts (rather than proportions) in the two categories  the O's  is easier to use and avoids possible roundoff errors due to obtaining proportions. The two will give exactly the same value for Z excepting rounding errors.
Obtain this quantity, find the normal tailarea corresponding to it, and double this tail area (both directions of difference are important) to get the Pvalue.
The question is: Are Al Gore and George Bush in a statistical tie? Use 5% as your error rate in deciding.
Clearly the two are not in an exact tie, either for the poll (Gore has a bit of a lead) or for the population as a whole (it would be extraordinary if two candidates were exactly tied over the entire nation of some 100,000,000 voters).
Let P_{G} be the true proportion of people for Gore; P_{B} the proportion of people for Bush. We test:
H_{0}: P_{G}  P_{B} = 0 H_{A}: P_{G } P_{B} ¹ 0 .
Note that more than 10 fall into each of the Gore and Bush categories, so this procedure may be used. Using the first expression for Z
Estimated difference:  .2318  .2112 = .0206. 
Standard error of estimated difference:  .0181. 
So, the test statistic is Z = .0206/.0181 = 1.1412. Tail area: .1269. Pvalue = 2*.1269 = .2538 or 25.38%. Decision: Do not reject H_{0} at the 5% significance level. This is equivalent to a statistical tie. At this point Gore and Bush are in a statistical tie.
Care to try some exercises on determining statistical ties?