1. What is Sample Mean?

The sample mean is the average value of a set of numbers. It's calculated by summing all the values in a dataset and dividing by the number of values. The sample mean is a fundamental measure of central tendency in statistics.

2. How Does the Calculator Work?

The calculator uses the sample mean formula:

Where:

• \( x_i \) — Individual data points
• \( n \) — Number of data points
• \( \sum \) — Summation of all values

Explanation: The formula calculates the arithmetic average of all values in the sample dataset.

3. Importance of Sample Mean

Details: The sample mean is crucial for statistical analysis as it provides a central value around which data points are distributed. It's used in hypothesis testing, quality control, and many other statistical applications.

4. Using the Calculator

Tips: Enter numeric values separated by commas (e.g., 5, 8, 12, 3, 9). The calculator will ignore any non-numeric values in the input.

5. Frequently Asked Questions (FAQ)

Q1: What's the difference between sample mean and population mean?
A: Sample mean is the average of a subset (sample) of data, while population mean is the average of all data in the population.

Q2: When should I use sample mean?
A: Use sample mean when you need to estimate the central tendency of a dataset, especially when working with samples rather than complete populations.

Q3: Is sample mean affected by outliers?
A: Yes, the sample mean is sensitive to extreme values. Consider using median for datasets with significant outliers.

Q4: Can I calculate sample mean for categorical data?
A: No, sample mean is only meaningful for numerical (quantitative) data.

Q5: How accurate is the sample mean as an estimator?
A: The sample mean is an unbiased estimator of the population mean, and its accuracy improves with larger sample sizes.