Plan an equal-size two-sample study

Choose the number of observations per group for a planned mean comparison.

Guides · Basic statistics · 4 min read

Example: two equal-size sachet-fill groups

Plan two independent fill groups with equal sample sizes. Detect a 1.5 g mean difference with common SD 4 g and 90% power. The reference scenario is adapted to equal allocation.

Download the planning reference (CSV)

This is the same example used in Help. The CSV lists reference scenarios. Enter the selected planning values manually on Inputs; importing it does not configure this calculator. Use Open example in a practice copy in Help to prefill the inputs.

1. Create the workspace

In the sidebar, open Basic Statistics and choose Power & Sample Size. Create an analysis, name it, select New blank worksheet, then choose Create analysis.

2. Choose the study

On Inputs, choose Two-sample t — pooled planning for Test and Sample size for Solve for. Enter 0.05 in Significance level (α) and choose Two-sided for Alternative hypothesis.

3. Enter the planning values

Enter one value in each field for this scenario. No worksheet columns are assigned.

Enter 4 in Common standard deviation (σ).

Enter 1.5 in Mean differences.

Enter 0.9 in Target powers.

Power & Sample Size: Inputs with the example’s assignments and settings
Inputs with the selected test, quantity to calculate and active planning assumptions. View full-size image (opens in a new tab)

4. Run analysis

Choose Run analysis, then open Results.

5. Interpret results

  1. Check the planned study

    Plan two independent fill groups with equal sample sizes. Detect a 1.5 g mean difference with common SD 4 g and 90% power. The reference scenario is adapted to equal allocation.

  2. Read the calculated plan

    Collect 151 observations per group, 302 total, under the stated common-SD and equal-allocation assumptions. Achieved power is about 90.11%; at 150 per group it is about 89.92%, below the 90% target.

  3. Follow the power curve

    The curve holds the sample size at 151 per group. Power reaches about 90% at a mean difference of +1.5 g or −1.5 g.

    Power versus effect
    Power versus effect View full-size chart (opens in a new tab)
  4. Understand the assumptions

    Power is the chance that the planned test detects the specified difference when that difference is real, under the entered assumptions. It is not the chance that a hypothesis is true and does not guarantee a significant result. This is pooled t-test planning for independent normal groups with a common SD and equal sizes. It does not plan a Welch test or unequal allocation.

  5. Decide how to collect the sample

    Confirm the common-SD assumption and the 1.5 g difference of interest. Reserve enough measurements for both groups and recalculate if their allocation or expected spread changes.

More details: read each result section

Complete result tables use six significant digits, as in Help.

Power and sample size scenarios

Scenario links this row to its input values. Branch records a solved effect direction; a dash means it is not applicable. Sample size is per group for two-group plans; Total observations counts both groups. Mean difference or Comparison proportion is the effect being planned. Target power is the request; Achieved power is the calculated result. Power at preceding size checks one fewer observation per group. DF is the t-test degrees of freedom, where applicable. Status and Details record whether the scenario was calculated. The plan requires 151 observations per group: 302 total. Achieved power is 0.901125. At 150 per group, it is 0.899225, below the 0.9 target.

Power and sample size scenarios · 1 row
ScenarioBranchSample size per groupTotal observationsMean differenceTarget powerAchieved powerPower at preceding sizeDFStatusDetails
1—1513021.50.90.9011250.899225300ok—
  • Unavailable branches retain their status and input values. Pairs count two observations each. A preceding-size power is reported only when that size is valid.

Planning method

Method and Calibration identify the calculation used. Alpha 0.05 is the test significance level; Alternative two-sided includes both directions. Solve for names the quantity being calculated. Assumptions and Planning SD or Baseline proportion record what the result depends on. This is pooled t-test planning for independent normal groups with a common SD and equal sizes. It does not plan a Welch test or unequal allocation.

Planning method · 7 rows
SettingValue
MethodTwo-sample t
Calibrationpooled-noncentral-t-v1
Alpha0.05
Alternativetwo-sided
Solve forSample size per group
AssumptionsIndependent normal groups; common SD; equal sizes; pooled-test planning.
Planning SD4
  • Results and curve points are captured with this run. Sample sizes are whole numbers; target power and achieved power are distinct.

Scenario input values

Scenario matches the numbered result row. Inputs records the active scenario values; these are planning assumptions, not observed measurements. Single-value inputs produce one scenario here.

Scenario input values · 1 row
ScenarioInputs
1{"delta":1.5,"power":0.9}

Captured power curve values

Each row gives a sample size, a mean difference or comparison proportion, and its calculated Power. These are all captured values behind the native chart. For two-group plans the size is per group. Read power between zero and one; 0.9 means 90%. The curve holds the sample size at 151 per group. Power reaches about 90% at a mean difference of +1.5 g or −1.5 g.

Captured power curve values · 61 rows
Sample size per groupMean differencePower
151-2.50.999723
151-2.416670.999468
151-2.333330.999007
151-2.250.998204
151-2.166670.996848
151-2.083330.99463
151-20.991121
151-1.916670.985745
151-1.833330.977771
151-1.750.966323
151-1.666670.950413
151-1.583330.929006
151-1.50.901125
151-1.416670.865972
151-1.333330.823066
151-1.250.77237
151-1.166670.714385
151-1.083330.650181
151-10.581368
151-0.9166670.509975
151-0.8333330.438283
151-0.750.368613
151-0.6666670.303113
151-0.5833330.243579
151-0.50.191333
151-0.4166670.147189
151-0.3333330.111485
151-0.250.08419
151-0.1666670.0650492
151-0.08333330.0537382
15100.05
1510.08333330.0537382
1510.1666670.0650492
1510.250.08419
1510.3333330.111485
1510.4166670.147189
1510.50.191333
1510.5833330.243579
1510.6666670.303113
1510.750.368613
1510.8333330.438283
1510.9166670.509975
15110.581368
1511.083330.650181
1511.166670.714385
1511.250.77237
1511.333330.823066
1511.416670.865972
1511.50.901125
1511.583330.929006
1511.666670.950413
1511.750.966323
1511.833330.977771
1511.916670.985745
15120.991121
1512.083330.99463
1512.166670.996848
1512.250.998204
1512.333330.999007
1512.416670.999468
1512.50.999723
  • All captured curves are included in this table and its CSV export; the plot shows at most 12 selected sample sizes.

6. Create a report

Keep Power and sample size scenarios, Planning method, Scenario input values, the native Power versus effect chart and its complete captured-values table. Record the difference worth detecting, planning spread or proportions, sample allocation and method. This is pooled t-test planning for independent normal groups with a common SD and equal sizes. It does not plan a Welch test or unequal allocation.

Choose Add to report from the completed run. Open Choose individual items and advanced options to select tables and charts, then choose Add to draft. Hidden items stay in the saved analysis.

Name the report and add the purpose of the study and your interpretation. Choose Save, review Preview, then use Export → Download HTML. The example below contains the full selected content, including results beyond one screen.

Complete native output for this Help example, including applicable tables, charts and run notes. Report numbers use the app’s displayed precision. Exported charts are static. On narrow screens, scroll wide charts and tables sideways.
View example report: Plan an equal-size two-sample study

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