A p-value is a number that tells us how likely it is to see data like what we have, if there's actually no effect or difference (the null hypothesis is true).
The p-value from the experiment was 0.03, which means there's a strong chance the null hypothesis is not true.
The p-value helps us decide if our findings are important. A smaller p-value means there's less chance that the results happened by chance, and more reason to believe the null hypothesis is false.
Scientists often use a p-value of 0.05 as a cutoff to say the results are statistically significant, meaning they're probably not due to random chance.