Condition on the total of 400 complaints. Assume each complaint independently has the same probability of being received on Monday; in particular, repeated complaints from one incident must not create material dependence. The Monday count then has a binomial distribution with parameters . Test against , rejecting for large as suggested by the monotone likelihood ratio.
Under the null hypothesis, and . Both expected successes and expected failures are large, so the central limit theorem gives a suitable normal approximation:
Using the paper's supplied rounded table, the upper-tail p-value is approximately
A more accurate evaluation of the standard normal distribution cumulative distribution function gives about 0.0062. For example, choose significance level 0.05 before examining the data; the supplied upper 5% standard normal quantile is approximately 1.6, and . Reject at 5%, and also at 1%, using this approximation. The observed binomial proportion is , providing evidence that the Monday probability exceeds 0.2 under the sampling assumptions.
If applying a continuity correction, approximate by ; this gives the same 5% and 1% conclusions. The uncorrected value 0.005 is approximate, so a decision exactly at the 0.5% boundary is not warranted by the supplied rounded table.

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