Two-Tailed Test
A two-tailed test is a statistical procedure used to compare the null hypothesis (that a population parameter is equal to a particular value) against the alternative hypothesis (that the population parameter is different from this value). Evidence regarding the null hypothesis is obtained from a test statistic, and the test is said to be “two tailed” because its alternative hypothesis does not specify whether the parameter is greater than or less than the value specified by the null hypothesis. Hence, both large and small values of the test statistic, that is, values on both tails of its distribution, provide evidence against the null hypothesis. This type of test is relevant for situations in which researchers wish to test a null hypothesis, but they do not ...
Looks like you do not have access to this content.
Reader's Guide
Descriptive Statistics
Distributions
Graphical Displays of Data
Hypothesis Testing
Important Publications
Inferential Statistics
Item Response Theory
Mathematical Concepts
Measurement Concepts
Organizations
Publishing
Qualitative Research
Reliability of Scores
Research Design Concepts
Research Designs
Research Ethics
Research Process
Research Validity Issues
Sampling
Scaling
Software Applications
Statistical Assumptions
Statistical Concepts
Statistical Procedures
Statistical Tests
Theories, Laws, and Principles
Types of Variables
Validity of Scores
- All
- A
- B
- C
- D
- E
- F
- G
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- X
- Y
- Z