Roy Morgan was the most accurate poll on the NSW election – same as last year’s Victorian Election
The New South Wales two-party preferred election result shows the ALP on 53.8% ahead of the L-NP on 46.2% (at 1pm on Tuesday March 28, 2023, with 63.4% of the vote counted). The final Roy Morgan SMS Poll conducted in mid-March and released on March 21, 2023 (available to view here) showed the ALP on 53.5% ahead of the L-NP on 46.5% and set to win the weekend’s New South Wales election with a minority government the most likely outcome.
The typical voting trends as postal and pre-poll votes are counted tend to favour the Coalition side of politics and this is set to drive the final two-party preferred result closer to the final Roy Morgan Poll.
The New South Wales election result is a strong endorsement of the accuracy provided by Roy Morgan SMS Polls and backs up the exact result predicted at last year’s Victorian election.
The final Roy Morgan SMS Poll prior to the Victorian election released on November 23, 2022 (available to view here) predicted a final two-party preferred result in Victoria of ALP 55% cf. L-NP 45% - this turned out to be exactly in line with last year’s Victorian election result.
The Roy Morgan SMS Polls have proved their value and strength in providing a quick and accurate representation of the mood of the electorate – the most accurate pre-election polls for both the New South Wales election and Victorian election.
Margin of Error
The margin of error to be allowed for in any estimate depends mainly on the number of interviews on which it is based. Margin of error gives indications of the likely range within which estimates would be 95% likely to fall, expressed as the number of percentage points above or below the actual estimate. Allowance for design effects (such as stratification and weighting) should be made as appropriate.
Sample Size | Percentage Estimate |
40% – 60% | 25% or 75% | 10% or 90% | 5% or 95% | |
1,000 | ±3.0 | ±2.7 | ±1.9 | ±1.3 |
5,000 | ±1.4 | ±1.2 | ±0.8 | ±0.6 |
7,500 | ±1.1 | ±1.0 | ±0.7 | ±0.5 |
10,000 | ±1.0 | ±0.9 | ±0.6 | ±0.4 |
20,000 | ±0.7 | ±0.6 | ±0.4 | ±0.3 |
50,000 | ±0.4 | ±0.4 | ±0.3 | ±0.2 |