Welcome to the Analytix Thinking blog! The blog that is intended to help people think rightly about data and deciding what is true. First, the intended audience is those who are analytically/quantitatively minded, but the exposition is also meant to be consumable by those who are curious about such matters, but without formal mathematical, statistical … Continue reading No. 1: Introduction – Welcome to Analytix Thinking
Implicit models in the back of our minds can creep into explicit models creating biased predictions that have societal implications.
If we fail to acknowledge that we have biases and assumptions that influence our assessment of 'objective facts,' then we delude ourselves. Our perception of reality and how we judged evidence is colored by our beliefs which arise from our spedific experiences.
The probability that the null hypothesis is true is 0.50. How should we interpret that and then write it down mathematically?
You may have heard, “Always do subgroup analysis, but never believe them.” Don't believe this.
The over-reliance on p-values can lead to misinterpretation of data and a $150 million bet on a subgroup with scant evidence.
How do we know when an observed effect is real or spurious?
Some people say, "A p-value=0.05 is not very much evidence against the null hypothesis." Well then, how much evidence is it?