1. What is Sum of Squares Total (SST)?

The Sum of Squares Total (SST) measures the total variation in a dataset from the mean. It's a fundamental concept in statistics used in analysis of variance (ANOVA), regression analysis, and other statistical methods.

2. How Does the Calculator Work?

The calculator uses the SST formula:

Where:

• \( X_i \) — Individual data point (unitless)
• \( \bar{X} \) — Mean of the data (unitless)
• \( \sum \) — Summation of all data points

Explanation: The formula calculates the squared difference between each data point and the mean, then sums all these squared differences.

3. Importance of SST Calculation

Details: SST is crucial for understanding data variability, calculating variance and standard deviation, and is the foundation for ANOVA which compares group means.

4. Using the Calculator

Tips: Enter your numerical data points separated by commas. The calculator will compute both the mean and the SST. Example: "5, 7, 8, 4, 6".

5. Frequently Asked Questions (FAQ)

Q1: What's the difference between SST, SSR, and SSE?
A: SST is total variation, SSR (Regression) is explained variation, and SSE (Error) is unexplained variation. SST = SSR + SSE.

Q2: Can SST be negative?
A: No, because it's a sum of squared values which are always non-negative.

Q3: How does SST relate to variance?
A: Variance = SST/(n-1) for sample variance or SST/n for population variance.

Q4: What does a high SST value indicate?
A: High SST indicates greater variability in the data points from the mean.

Q5: Is SST affected by outliers?
A: Yes, because the differences are squared, outliers have a disproportionate effect on SST.