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Sample Size Formula for Means:
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Sample size calculation is a crucial step in research design that determines the number of participants needed to detect a statistically significant effect. For thesis research, proper sample size ensures the study has adequate power to test hypotheses while minimizing resource waste.
The calculator uses the sample size formula for means estimation:
Where:
Explanation: This formula calculates the minimum number of participants needed to estimate a population mean with specified precision and confidence level.
Details: Proper sample size calculation prevents underpowered studies (Type II errors) and overpowered studies (resource waste). It ensures research validity and credibility for thesis defense and publication.
Tips: Enter Z-score based on confidence level (1.96 for 95%, 2.576 for 99%), estimated standard deviation from pilot studies or literature, and desired margin of error. All values must be positive.
Q1: What Z-score should I use for my thesis?
A: For most academic research, use Z=1.96 for 95% confidence level. For higher precision, use Z=2.576 for 99% confidence.
Q2: How do I estimate standard deviation?
A: Use data from pilot studies, previous similar research, or literature reviews. If unavailable, conduct a small pilot study first.
Q3: What is an acceptable margin of error?
A: Typically 5% of the mean value, but this depends on research context and precision requirements of your field.
Q4: Should I adjust for expected dropout rate?
A: Yes, multiply calculated sample size by 1/(1-dropout rate). For 20% expected dropout: n_adjusted = n / 0.8.
Q5: Is this formula appropriate for all study designs?
A: This formula is for simple random sampling. Complex designs (cluster, stratified) require additional adjustments.