Sample Size Calculation for Time Series Analysis
Introduction & Importance
Sample size calculation for time series analysis is crucial for ensuring your study has enough power to detect significant effects…
How to Use This Calculator
- Enter the desired power, significance level, effect size, and standard deviation.
- Click ‘Calculate’.
- View the results below the calculator.
Formula & Methodology
The formula used in this calculator is based on the work of Cohen (1988)…
Real-World Examples
Example 1: Stock Market Analysis
In a study of daily stock returns, a researcher wants to detect an effect size of 0.5 with 80% power and a significance level of 0.05…
Data & Statistics
| Effect Size | Power (α = 0.05) |
|---|---|
| 0.2 | 0.09 |
| 0.5 | 0.8 |
| 0.8 | 0.99 |
| Power | Sample Size |
|---|---|
| 0.6 | 25 |
| 0.7 | 36 |
| 0.8 | 50 |
Expert Tips
- Always consider the practical implications of your chosen sample size.
- Be aware of the assumptions behind the formula used in this calculator.
Interactive FAQ
What is power in the context of time series analysis?
Power in time series analysis refers to the probability of detecting a significant effect when there is one…
How does the significance level (α) affect the sample size?
A lower significance level requires a larger sample size to maintain the same power…
UK Statistics Authority and CDC provide more information on statistical methods.