Check power for a fixed sample

Estimate the chance of detecting a specified difference with an available sample size.

Guides · Basic statistics · 4 min read

Example: fifty sachets per group

Two independent groups can each supply 50 sachet-fill measurements. Assume common SD 4 g and a true mean difference of 1.5 g.

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 Power 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 50 in Sample sizes per group.

Enter 1.5 in Mean differences.

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

    Two independent groups can each supply 50 sachet-fill measurements. Assume common SD 4 g and a true mean difference of 1.5 g.

  2. Read the calculated plan

    Achieved power is 0.458911, about 45.9%, for 50 per group (100 total). Under the assumptions, the test would miss this real difference in about 54.1% of comparable studies.

  3. Follow the power curve

    The curve holds sample size at 50 per group. At ±1.5 g it reaches about 45.9%; larger differences are easier to detect.

    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 pooled t-test plan assumes independent normal groups, equal sizes and common SD 4 g. A nonsignificant study with this power would not establish equal means.

  5. Decide how to collect the sample

    With 50 per group, a real 1.5 g difference would be detected in about 45.9% of comparable studies and missed in about 54.1%, under the planning assumptions. For a higher target, choose Sample size in Solve for, enter the target power and rerun. If the sample is fixed, report this limited sensitivity.

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. Achieved power is 0.458911, about 45.9%, for 50 per group (100 total). Under the assumptions, the test would miss this real difference in about 54.1% of comparable studies.

Power and sample size scenarios · 1 row
ScenarioBranchSample size per groupTotal observationsMean differenceTarget powerAchieved powerPower at preceding sizeDFStatusDetails
1—501001.5—0.458911—98ok—
  • 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 pooled t-test plan assumes independent normal groups, equal sizes and common SD 4 g. A nonsignificant study with this power would not establish equal means.

Planning method · 7 rows
SettingValue
MethodTwo-sample t
Calibrationpooled-noncentral-t-v1
Alpha0.05
Alternativetwo-sided
Solve forPower
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{"n":50,"delta":1.5}

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 sample size at 50 per group. At ±1.5 g it reaches about 45.9%; larger differences are easier to detect.

Captured power curve values · 61 rows
Sample size per groupMean differencePower
50-2.50.871659
50-2.416670.848762
50-2.333330.823299
50-2.250.79528
50-2.166670.764775
50-2.083330.731915
50-20.696893
50-1.916670.659962
50-1.833330.621428
50-1.750.581649
50-1.666670.541019
50-1.583330.499961
50-1.50.458911
50-1.416670.418307
50-1.333330.378575
50-1.250.340115
50-1.166670.303291
50-1.083330.268423
50-10.23578
50-0.9166670.205575
50-0.8333330.177967
50-0.750.15306
50-0.6666670.13091
50-0.5833330.111532
50-0.50.0949054
50-0.4166670.0809875
50-0.3333330.0697201
50-0.250.0610404
50-0.1666670.0548895
50-0.08333330.0512197
5000.05
500.08333330.0512197
500.1666670.0548895
500.250.0610404
500.3333330.0697201
500.4166670.0809875
500.50.0949054
500.5833330.111532
500.6666670.13091
500.750.15306
500.8333330.177967
500.9166670.205575
5010.23578
501.083330.268423
501.166670.303291
501.250.340115
501.333330.378575
501.416670.418307
501.50.458911
501.583330.499961
501.666670.541019
501.750.581649
501.833330.621428
501.916670.659962
5020.696893
502.083330.731915
502.166670.764775
502.250.79528
502.333330.823299
502.416670.848762
502.50.871659
  • 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 pooled t-test plan assumes independent normal groups, equal sizes and common SD 4 g. A nonsignificant study with this power would not establish equal means.

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: Find power with 50 per group

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