লক্ষ্য করুন: এই এন্ট্রির অনুবাদ বর্তমানে মান পর্যালোচনার অধীনে রয়েছে, তাই কিছু বিষয়বস্তু সাময়িকভাবে শুধুমাত্র ইংরেজিতে প্রদর্শিত হচ্ছে।
এই এন্ট্রিটি এখনও আপনার ভাষায় অনুবাদ করা হয়নি, তাই নিচে মূল লেখাটি দেখানো হচ্ছে।
p value
This term is a technical statistic used primarily in hypothesis testing to determine whether an observed effect is likely due to chance. It carries a neutral, scientific register and is almost exclusively found in academic papers, clinical trial reports, and data analysis contexts.
Users should be cautious not to confuse a low p value with the magnitude of an effect; a result can be statistically significant without being practically meaningful. In professional discourse, it is frequently paired with a significance level, typically denoted as alpha, to decide whether to reject a null hypothesis.
Meanings
Examples
The p value was below 0.05, so we rejected the null hypothesis.
I wonder if this p value is actually meaningful or just a result of a huge sample size.
We need to calculate the p value before submitting the paper to the journal.
A low p value does not necessarily mean the effect size is large.
The clinical trial showed a p value of 0.01 for the new drug treatment.
Wait, did you check if the p value was adjusted for multiple comparisons?
The researcher noted that the p value was barely significant.
The researcher noted that the p value was barely significant.
If the p value is greater than 0.05, we fail to reject the null hypothesis.