Statistic
Table of Contents
What is a Statistic?
A statistic is a numerical value calculated from sample data that provides information about a specific sample aspect. Statistics estimate population parameters, describe sample characteristics and compare and test hypotheses.
Unlike parameters, which are fixed values that describe populations, statistics can vary from one sample to another and are used to conclude populations based on sample data.
Types of Statistics
- Descriptive Statistics: These statistics describe and summarize characteristics of the sample data, such as measures of central tendency (mean, median, mode), measures of dispersion (variance, standard deviation, range), and measures of position (percentiles, quartiles).
- Inferential Statistics: These statistics are used to make inferences, predictions, and generalizations about populations based on sample data. They include point estimates, interval estimates (confidence intervals), and hypothesis tests.
Examples of Statistics
- Sample Mean (\bar{x}): The average value of observations in a sample.
- Sample Variance (s^2): A measure of the spread or dispersion of data points around the sample mean.
- Sample Proportion: (\hat{p}): The proportion of individuals in a sample that has a specific characteristic or belongs to a particular category.
- Test Statistic: A statistic calculated in hypothesis testing to determine the likelihood of obtaining sample results under the null hypothesis.
Role of Statistics
- Statistics are used to estimate unknown population parameters using sample data. For example, the sample mean (\bar{x}) is often used as an estimate of the population mean (\mu).
- Statistics provide information about the sample data’s variability, distribution, and relationships, which can be used to make informed decisions and draw conclusions.
Related Links
Causation
Parameter
Population vs. Sample
Snowball Sampling