Hypothesis, causality, and tails

Hypothesis, causality, and tails

1. Using regression analysis, we can predict or estimate what may happen, regression does not give us any proof about causality.

2. Our theory ought to contain a constellation where there is, an exhastive hypothetical reason for expecting causality between the independent and the dependent varible.

3. If causality between variables A and B can be antivipated, in which A and B we have a 1-tailed hypothesis. If our hypothesis is 2-tailed, where A can affect B or B affects A, we have to check for significance in both directions.

4. H0 there is no connection between social status and use of non-standard forms.the objective of our research is to neglete or demostrate the H0.

   • HA: there is no connection between social status and use of non-standard forms.
     • the Pearson connection will tell us if there is a connection between the two scores, which course it takes, and how solid it is.

5. The T-test

   • permits us to analyze the scores, The T-test is a statistical method that contrasts the arithmetic means of 2 groups of information while taking their variability, it permits to reach inferences whether there is genuine contrast between 2 groups.
     • The T-test must be applied to normally distributed data and preferability be applied in the event that we have at any rate ten items.
   • Independent samples for T-test.
     • Hypothesis: H0; There is no contrast between the experimental groups and the control group. HA; there is no connection between EG and CG after the stimulus was stabished.
   • Dependent T-test