# Statistical Terms

Statistics plays a critical role in many fields, making it essential to understand key statistical terms. Knowing statistical terms helps in interpreting data accurately and making informed decisions. This reference allows individuals to grasp complex information quickly and apply it effectively in various situations.

Contents

## What Are Statistical Terms?

Statistics is the study of collecting, analyzing, interpreting, presenting, and organizing data. It helps make decisions based on data patterns and relationships.

Statistical terms enable clear communication of data findings. They help in identifying trends, making predictions, and testing hypotheses. By learning these terms, anyone can better navigate research papers, reports, and daily news that involve data analysis.

## List of Statistical Terms

• Mean
• Median
• Mode
• Range
• Variance
• Standard Deviation
• Probability
• Population
• Sample
• Confidence Interval
• Hypothesis
• P-Value
• Correlation
• Regression
• Outlier
• Skewness
• Kurtosis
• Normal Distribution
• Bias
• Random Variable
• Null Hypothesis

## Common Statistical Terms with Meanings

Mean: The average of a set of numbers. Calculate it by adding all numbers and dividing by the count of numbers.

Median: The middle value in a list of numbers. Arrange the numbers in order, then find the central number.

Mode: The number that appears most frequently in a data set.

Range: The difference between the highest and lowest values in a set.

Variance: Measures how spread out the numbers in a data set are.

Standard Deviation: A measure of the amount of variation or dispersion in a set of values. It is the square root of the variance.

Probability: The chance that a particular event will happen. It ranges from 0 to 1.

Correlation: A measure of the relationship between two variables. It can be positive, negative, or zero.

Sample: A subset of a larger population used to represent the whole group.

Population: The entire group that a researcher wants to study.

Hypothesis: A testable statement about the relationship between two or more variables.

P-value: The probability that the observed results are due to chance. A p-value less than 0.05 often indicates statistical significance.

Confidence Interval: A range of values that is likely to contain the population parameter. It provides an estimate and a measure of uncertainty.

Regression: A method for modeling the relationship between a dependent variable and one or more independent variables.

Outlier: An observation that is significantly different from other values in a data set. It can affect results and must sometimes be investigated further.