2010–11 MacroMonitor Sampling Tolerance Tables
Sampling Tolerance for Individual Percentages
Sampling Tolerance for Individual Percentages |
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|---|---|---|---|---|---|
| Approximate Sampling Tolerance for a Survey Percentage at or near These Levels | |||||
| Size of Sample on Which Survey Result Is Based |
10% or 90% | 20% or 80% | 30% or 70% | 40% or 60% | 50% |
| 3600 | 2% | 2% | 3% | 3% | 3% |
| 2500 | 2 | 3 | 3 | 3 | 3 |
| 1700 | 2 | 3 | 4 | 4 | 4 |
| 850 | 3 | 4 | 5 | 5 | 5 |
| 700 | 4 | 5 | 6 | 6 | 6 |
| 500 | 4 | 6 | 6 | 7 | 7 |
| 175 | 7 | 10 | 11 | 12 | 12 |
| 100 | 10 | 12 | 13 | 14 | 14 |
How to Use This Table
Use this table when you are trying to determine if a statistically significant difference exists between two percentages in the same sample. Look at this chart for the column closest to the two percentages. Look for the row that is closest to the unweighted sample size. At the location where they cross is a number that must be smaller than the gap between the two percentages. For example, if you were looking at a question where 32% of the respondents had selected one answer and 28% had selected another and where the sample consisted of 2235 unweighted respondents, you would look at where the 30% column intersected with the 2500 sample and find 3%. Because the gap between 28% and 32% is greater than 3%, these two numbers are statistically significant. Put another way: Significantly more respondents selected the 32% answer than the 28% answer.
Testing Two-Sample Statistical Significance at the 95% Confidence Interval for Percentages of 10% and 90%
Table for Testing Two-Sample Statistical Significance at the 95% Confidence Interval for Percentages of 10% and 90% |
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|---|---|---|---|---|---|---|---|---|
| Sample Size | 3500 | 2000 | 1500 | 1000 | 750 | 500 | 250 | 100 |
| 3500 | 1.7% | 1.8% | 1.9% | 2.2% | 2.4% | 2.8% | 3.8% | 5.9% |
| 2000 | 1.8 | 1.9 | 2.0 | 2.3 | 2.5 | 2.9 | 3.9 | 6.0 |
| 1500 | 1.9 | 2.0 | 2.1 | 2.4 | 2.6 | 3.0 | 4.0 | 6.1 |
| 1000 | 2.2 | 2.3 | 2.4 | 2.6 | 2.8 | 3.2 | 4.2 | 6.2 |
| 750 | 2.4 | 2.5 | 2.6 | 2.8 | 3.0 | 3.4 | 4.3 | 6.3 |
| 500 | 2.8 | 2.9 | 3.0 | 3.2 | 3.4 | 3.7 | 4.6 | 6.4 |
| 250 | 3.8 | 3.9 | 4.0 | 4.2 | 4.3 | 4.6 | 5.3 | 7.0 |
| 100 | 5.9 | 6.0 | 6.1 | 6.2 | 6.3 | 6.4 | 7.0 | 8.3 |
How to Use This Table
Use this table when you are trying to determine if a statistically significant difference exists between two percentages that are close to 10% or 90% of different (sub) samples. First, determine the unweighted sample sizes for the two populations. Next, look at the above chart for the intersection that comes closest to the two unweighted sample sizes. Finally, if the gap between the two percentages that you have is larger than the number in the intersection, then the two percentages are statistically different at the 95% confidence interval. For example, suppose the two percentages that you are comparing are 8% and 12% and the unweighted sample sizes are 431 and 728, respectively. Looking at the table above, the closest intersection of these numbers occurs at the 500 and 750 sample sizes. The number in this cell is 3.4%. The gap between the two percentages is 4%. Therefore, the difference is statistically significant.
Testing Two-Sample Statistical Significance at the 95% Confidence Interval for Percentages of 20% and 80%
Table for Testing Two-Sample Statistical Significance at the 95% Confidence Interval for Percentages of 20% and 80% |
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|---|---|---|---|---|---|---|---|---|
| Sample Size | 3500 | 2000 | 1500 | 1000 | 750 | 500 | 250 | 100 |
| 3500 | 2.3% | 2.4% | 2.6% | 2.9% | 3.3% | 3.8% | 5.2% | 7.9% |
| 2000 | 2.4 | 2.5 | 2.7 | 3.0 | 3.4 | 3.9 | 5.3 | 8.0 |
| 1500 | 2.6 | 2.7 | 2.9 | 3.2 | 3.5 | 4.0 | 5.4 | 8.1 |
| 1000 | 2.9 | 3.0 | 3.2 | 3.5 | 3.8 | 4.3 | 5.5 | 8.2 |
| 750 | 3.3 | 3.4 | 3.5 | 3.8 | 4.0 | 4.5 | 5.7 | 8.3 |
| 500 | 3.8 | 3.9 | 4.0 | 4.3 | 4.5 | 5.0 | 6.1 | 8.6 |
| 250 | 5.2 | 5.3 | 5.4 | 5.5 | 5.7 | 6.1 | 7.0 | 9.3 |
| 100 | 7.9 | 8.0 | 8.1 | 8.2 | 8.3 | 8.6 | 9.3 | 11.0 |
How to Use This Table
Use this table when you are trying to determine if a statistically significant difference exists between two percentages that are close to 20% or 80% of different (sub) samples. First, determine the unweighted sample sizes for the two populations. Next, look at the above chart for the intersection that comes closest to the two unweighted sample sizes. Finally, if the gap between the two percentages that you have is larger than the number in the intersection, then the two percentages are statistically different at the 95% confidence interval. For example, suppose the two percentages that you are comparing are 18% and 22% and the unweighted sample sizes are 431 and 728, respectively. Looking at the table above, the closest intersection of these numbers occurs at the 500 and 750 sample sizes. The number in this cell is 4.5%. The gap between the two percentages is 4%. Therefore, the difference is not statistically significant.
Testing Two-Sample Statistical Significance at the 95% Confidence Interval for Percentages of 30% and 70%
Table for Testing Two-Sample Statistical Significance at the 95% Confidence Interval for Percentages of 30% and 70% |
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|---|---|---|---|---|---|---|---|---|
| Sample Size | 3500 | 2000 | 1500 | 1000 | 750 | 500 | 250 | 100 |
| 3500 | 2.5% | 2.6% | 2.9% | 3.3% | 3.7% | 4.4% | 5.9% | 9.1% |
| 2000 | 2.6 | 2.8 | 3.1 | 3.5 | 3.8 | 4.5 | 6.0 | 9.2 |
| 1500 | 2.9 | 3.1 | 3.3 | 3.7 | 4.0 | 4.6 | 6.1 | 9.3 |
| 1000 | 3.3 | 3.5 | 3.7 | 4.0 | 4.3 | 4.9 | 6.4 | 9.4 |
| 750 | 3.7 | 3.8 | 4.0 | 4.3 | 4.6 | 5.2 | 6.6 | 9.6 |
| 500 | 4.4 | 4.5 | 4.6 | 4.9 | 5.2 | 5.7 | 7.0 | 9.8 |
| 250 | 5.9 | 6.0 | 6.1 | 6.4 | 6.6 | 7.0 | 8.0 | 10.6 |
| 100 | 9.1 | 9.2 | 9.3 | 9.4 | 9.6 | 9.8 | 10.6 | 12.7 |
How to Use This Table
Use this table when you are trying to determine if a statistically significant difference exists between two percentages that are close to 30% or 70% of different (sub) samples. First, determine the unweighted sample sizes for the two populations. Next, look at the above chart for the intersection that comes closest to the two unweighted sample sizes. Finally, if the gap between the two percentages that you have is larger than the number in the intersection, then the two percentages are statistically different at the 95% confidence interval. For example, suppose the two percentages that you are comparing are 68% and 72% and the unweighted sample sizes are 1431 and 728, respectively. Looking at the table above, the closest intersection of these numbers occurs at the 1500 and 750 sample sizes. The number in this cell is 4.0%. The gap between the two percentages is 4%. Therefore, the difference is not statistically significant. (The difference needs to be larger than the value in the cell.)
Testing Two-Sample Statistical Significance at the 95% Confidence Interval for Percentages of 40% and 60%
Table for Testing Two-Sample Statistical Significance at the 95% Confidence Interval for Percentages of 40% and 60% |
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|---|---|---|---|---|---|---|---|---|
| Sample Size | 3500 | 2000 | 1500 | 1000 | 750 | 500 | 250 | 100 |
| 3500 | 2.7% | 2.8% | 3.1% | 3.5% | 3.9% | 4.6% | 6.2% | 9.7% |
| 2000 | 2.8 | 3.0 | 3.3 | 3.7 | 4.1 | 4.8 | 6.4 | 9.8 |
| 1500 | 3.1 | 3.3 | 3.5 | 3.9 | 4.3 | 5.0 | 6.6 | 9.9 |
| 1000 | 3.5 | 3.7 | 3.9 | 4.3 | 4.6 | 5.3 | 6.8 | 10.0 |
| 750 | 3.9 | 4.1 | 4.3 | 4.6 | 5.0 | 5.5 | 7.0 | 10.2 |
| 500 | 4.6 | 4.8 | 5.0 | 5.3 | 5.5 | 6.1 | 7.4 | 10.5 |
| 250 | 6.2 | 6.4 | 6.6 | 6.8 | 7.0 | 7.4 | 8.6 | 11.4 |
| 100 | 9.7 | 9.8 | 9.9 | 10.0 | 10.2 | 10.5 | 11.4 | 13.6 |
How to Use This Table
Use this table when you are trying to determine if a statistically significant difference exists between two percentages that are close to 40% or 60% of different (sub) samples. First, determine the unweighted sample sizes for the two populations. Next, look at the above chart for the intersection that comes closest to the two unweighted sample sizes. Finally, if the gap between the two percentages that you have is larger than the number in the intersection, then the two percentages are statistically different at the 95% confidence interval. For example, suppose the two percentages that you are comparing are 38% and 42% and the unweighted sample sizes are 431 and 728, respectively. Looking at the table above, the closest intersection of these numbers occurs at the 500 and 750 sample sizes. The number in this cell is 5.0%. The gap between the two percentages is 4%. Therefore, the difference is not statistically significant.
Testing Two-Sample Statistical Significance at the 95% Confidence Interval for Percentages around 50%
Table for Testing Two-Sample Statistical Significance at the 95% Confidence Interval for Percentages around 50% |
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|---|---|---|---|---|---|---|---|---|
| Sample Size | 3500 | 2000 | 1500 | 1000 | 750 | 500 | 250 | 100 |
| 3500 | 2.8% | 2.9% | 3.1% | 3.6% | 4.0% | 4.7% | 6.5% | 9.9% |
| 2000 | 2.9 | 3.1 | 3.3 | 3.8 | 4.2 | 4.9 | 6.6 | 10.0 |
| 1500 | 3.1 | 3.3 | 3.6 | 4.0 | 4.4 | 5.1 | 6.7 | 10.1 |
| 1000 | 3.6 | 3.8 | 4.0 | 4.4 | 4.7 | 5.4 | 6.9 | 10.3 |
| 750 | 4.0 | 4.2 | 4.4 | 4.7 | 5.1 | 5.7 | 7.2 | 10.4 |
| 500 | 4.7 | 4.9 | 5.1 | 5.4 | 5.7 | 6.2 | 7.6 | 10.7 |
| 250 | 6.5 | 6.6 | 6.7 | 6.9 | 7.2 | 7.6 | 8.8 | 11.6 |
| 100 | 9.9 | 10.0 | 10.1 | 10.3 | 10.4 | 10.7 | 11.6 | 13.9 |
How to Use This Table
Use this table when you are trying to determine if a statistically significant difference exists between two percentages that are close to 50% of different (sub) samples. First, determine the unweighted sample sizes for the two populations. Next, look at the above chart for the intersection that comes closest to the two unweighted sample sizes. Finally, if the gap between the two percentages that you have is larger than the number in the intersection, then the two percentages are statistically different at the 95% confidence interval. For example, suppose the two percentages that you are comparing are 48% and 53% and the unweighted sample sizes are 1,431 and 728, respectively. Looking at the table above, the closest intersection of these numbers occurs at the 1500 and 750 sample sizes. The number in this cell is 4.4%. The gap between the two percentages is 5%. Therefore, the difference is statistically significant.
