A high t statistic does not indicate strong relationship between dependent variable and Independent variable

Gentle Reminder : A high t statistic does not indicate strong relationship of IVs with the DV.

Just the other day, I saw a post (again) stating that a t statistic indicates strength of relationship of IVs to DVs.

So here is a gentle reminder (sharing it again).

The high t statistic here does not indicate a strong relationship with the dependent variable.

We must first understand what is the null hypothesis in the current context. The null hypothesis is slope =0 or in other words the beta = 0.

The alternate hypothesis being, slope โ‰ 0.

So even if we reject the null, we still don’t get ‘quantification of the effect size’. All we know now is that ‘there is non zero effect’ but don’t know exactly how much.

So, pls stop inferring that “A high T statistic value indicates that the variable has a strong relationship with the dependent variable”.

Facebook
Twitter
LinkedIn

Recommended Posts

Chebyshev’s Inequality for Marketing Mix Model Diagnostics

Chebyshev’s Inequality for Marketing…

At Aryma Labs, we constantly endeavor to add as much science as possible…

How to use Robyn’s…

In my last post (ICYMI link in resources), I talked about the similarities…

Similarities between Decomp RSSD and Bayesian Priors in Marketing Mix Modeling (MMM)

Similarities between Decomp RSSD…

Open source Marketing Mix Modeling (MMM) tools are great for democratizing MMM. But…

Scroll to Top