1. What is the T Score?

The T Score is a statistical measure that indicates how many standard deviations a data point is from the mean of a sample, adjusted for sample size. It's commonly used in hypothesis testing and statistical analysis.

2. How Does the Calculator Work?

The calculator uses the T Score formula:

Where:

• \( x \) — Individual data point value
• \( \mu \) — Mean of the sample
• \( SD \) — Standard deviation of the sample
• \( n \) — Sample size

Explanation: The formula calculates how many standard errors a data point is from the mean, providing a standardized measure of deviation.

3. Importance of T Score Calculation

Details: T Scores are crucial for statistical hypothesis testing, determining statistical significance, and making inferences about population parameters based on sample data.

4. Using the Calculator

Tips: Enter the individual value, sample mean, standard deviation, and sample size. All values must be valid (SD > 0, n ≥ 1).

5. Frequently Asked Questions (FAQ)

Q1: What's the difference between T Score and Z Score?
A: T Score uses sample standard deviation and is used when population standard deviation is unknown, while Z Score uses population standard deviation.

Q2: When should I use T Score?
A: Use T Score for small sample sizes (typically n < 30) or when population standard deviation is unknown.

Q3: What does a high T Score indicate?
A: A high absolute T Score indicates that the data point is far from the mean, suggesting it may be statistically significant.

Q4: How is T Score related to p-value?
A: T Scores are used to determine p-values in t-tests. Higher absolute T Scores typically correspond to smaller p-values.

Q5: Can T Score be negative?
A: Yes, T Score can be negative when the data point is below the mean of the sample.