Lab Resources

General Resources

Palette Generator

Create beautiful color palettes for figures and visualizations. Click the first or last color to customize your palette endpoints.

Palette Type

Number of Colors

3 8

#003F5C

#58508D

#BC5090

#FF6361

#FFA600

In Context

DOI to Bibliography

Convert DOI to formatted citations in BibTeX, APA, MLA, or other formats. Paste any DOI and get publication-ready citations.

Enter DOI Digital Object Identifier (DOI):
Accepts DOIs in various formats:
• 10.1038/nature12373
• doi:10.1038/nature12373
• https://doi.org/10.1038/nature12373
• http://dx.doi.org/10.1038/nature12373

The tool will automatically handle different formats and retrieve bibliographic data directly from publishers via CrossRef.

Citation Format Citation Formats:
• BibTeX: For LaTeX documents and reference managers
• APA: American Psychological Association style
• MLA: Modern Language Association style
• Chicago: Chicago Manual of Style
• Vancouver: Common in medical journals
• Harvard: Author-date citation style

Format is retrieved directly from publisher metadata via CrossRef.

Citation

Power Analysis Calculator

Calculate statistical power, sample size, or effect size for t-tests. Enter any three parameters to calculate the fourth.

Test Type Statistical Test Type:
• Two Sample: Compare means between two independent groups (e.g., treatment vs control)
• One Sample: Compare a single group mean against a known value or hypothesis
• Paired: Compare paired observations (e.g., before/after measurements on same subjects)

Alternative Alternative Hypothesis:
• Two-sided: Effect could be in either direction (most common, tests if groups differ)
• Greater: One-sided test, expecting the first group to be larger
• Less: One-sided test, expecting the first group to be smaller

Two-sided tests are more conservative and generally recommended unless you have strong directional predictions.

Sample Size (n) Sample Size: Number of subjects per group (for two-sample) or total subjects (for one-sample/paired). This is what you need to determine for study planning, or what you actually collected for post-hoc analysis.

Planning tip: Larger samples detect smaller effects but require more resources. Aim for the minimum n that gives adequate power.

Effect Size (Cohen's d) Effect Size (Cohen's d): Standardized measure of the difference between groups.

Interpretation:
• |d| < 0.2: Negligible effect
• |d| = 0.2: Small effect
• |d| = 0.5: Medium effect
• |d| = 0.8: Large effect

Estimation sources: Previous literature, pilot studies, or theoretical expectations. Use the Cohen's d calculator below if you have means and SDs.

Alpha Level Alpha Level (α): Probability of Type I error - incorrectly rejecting a true null hypothesis (false positive rate).

Common values:
• 0.05 (5%): Standard in most fields
• 0.01 (1%): More stringent, reduces false positives
• 0.10 (10%): Less stringent, sometimes used in exploratory research

Lower α values require larger samples to maintain power.

Power (1-β) Statistical Power (1-β): Probability of correctly detecting a true effect when it exists (1 minus Type II error rate).

Common values:
• 0.80 (80%): Minimum acceptable in most fields
• 0.90 (90%): Higher standard, more stringent
• 0.95 (95%): Very high power, requires large samples

Higher power reduces the chance of missing real effects but requires larger sample sizes.

Results

Cohen's d Calculator

Calculate effect size from means and standard deviations using the formula: d = (M₁ - M₂) / pooled SD

Mean 1 Mean 1 (M₁): Average value for the first group or condition.

Examples:
• Control group mean
• Pre-treatment measurement
• Baseline condition average

Units should match Mean 2 for meaningful comparison.

Mean 2 Mean 2 (M₂): Average value for the second group or condition.

Examples:
• Treatment group mean
• Post-treatment measurement
• Experimental condition average

The difference (M₁ - M₂) determines the direction and magnitude of the effect.

SD 1 Standard Deviation 1: Measure of variability in the first group.

Important: Must be in same units as the means. Larger SD indicates more spread in the data.

Source: Calculate from your data using sample standard deviation (dividing by n-1), not population SD.

SD 2 Standard Deviation 2: Measure of variability in the second group.

Formula context: Both SDs are used to calculate the pooled standard deviation: √[(SD₁² + SD₂²)/2], which standardizes the mean difference.

This creates a unit-free effect size comparable across studies.

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Lab Resources

General Resources

Palette Generator

DOI to Bibliography

Citation

Power Analysis Calculator

Results

Cohen's d Calculator

Lab Resources

Colonies.

Live Data.

Keith's Zoom Room.

Lab Meeting Calendar.

Upcoming Lab Meetings

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