Intervals in Means

Significance test

A statistical method used to determine whether the observed data supports a hypothesis or if the results are due to chance. It assesses the likelihood that a particular outcome would occur if the null hypothesis were true.

Null hypthesis

The assumption that there is no significant effect or relationship in a set of data, which researchers aim to test against alternative hypotheses.

Alternative hypothesis

The hypothesis that suggests there is a significant effect or relationship in a set of data, opposing the null hypothesis. It is what researchers seek to support through testing.

One-sided alternative hypothesis

A type of hypothesis that tests for the possibility of the relationship in one direction only, indicating either an increase or decrease but not both. This is often used when the research predicts the direction of the effect.

Two-sided alternative hypothesis

A hypothesis that allows for the possibility of an effect in both directions, indicating that the parameter can be either greater than or less than a specified value. This type of hypothesis is used when researchers want to detect any difference, regardless of the direction.

P-values

Measures probability of observed study results if H0 is true, measures strength against null hypothesis.

Statistical significance

Refers to the likelihood that a relationship observed in data is caused by something other than random chance.

Significance level

We are requiring that the data ives evidence against Ho so strong that it would happen less than ___% the time if Ho is true.

Test statistic

How far a sample statistic diverges from what we expect if Ho = true