Hypothesis Test Components | Teradata Vantage - Hypothesis Test Components - Analytics Database

Database Analytic Functions

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Analytics Database
Release Number
17.20
Published
June 2022
Language
English (United States)
Last Update
2024-04-06
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Product Category
Teradata Vantage™

All hypothesis tests have the following components:

Component Description
Null hypothesis (H0)

The null hypothesis is known as a hypothesis of no difference.

Example: Experimental drug is no better than placebo.

The null hypothesis is accepted or rejected based on a statistical test of the hypothesis.

Alternate hypothesis (H1) Hypothesis accepted if null hypothesis is rejected.

Example: Experimental drug is more effective than placebo.

Alpha (α)

(Also called significance level or Type I error.)

The Null Hypothesis is rejected if the P-value is smaller than the specified Alpha value (where Alpha is the probability of rejecting the null hypothesis when it is true).

Most common α values are 0.01, 0.05, and 0.10, corresponding to 99%, 95%, and 90% confidence, respectively.

Results are "statistically significant at α."

Test statistic Value to which data set is reduced, used in hypothesis test. Its sampling distribution under null hypothesis must be calculable (exactly or approximately), making p_values calculable.
Degrees of freedom Number of independent pieces of information needed to estimate a population parameter (for example, μ or σ2) for sample of specified size.
Critical value Quantile of distribution of test statistic under null hypothesis. Used to determine rejection region.
p_value Probability of test results at least as extreme as test statistic results observed under assumption that null hypothesis is true.

The smaller the p_value, the stronger the evidence against the null hypothesis.

Hypothesis test conclusion Acceptance or rejection of null hypothesis.