The New Arena

[Bohemian Toffee]

When is the Guernsey Gobbler returning to blame Dele's child abuse on his imaginary cocaine habit?

After his imaginary beer, food, woman date yesterday.

 

[Prevenger17]

That was one weird lad. Imagine citing P values when you have absolutely no idea what they are

 

[Terrarian]

 

[lancs blue]

This is most definitely a sentence from a man who has never talked to a woman in their life

 

[Hinchcliffe's Corner]

 

[Blue 1]

church has a lot to answer for.
nitrous oxide is what some utter wank-muffin is calling 'hippy crack'. It's the equivalent of being strangled David Carradine style with less danger - or so I'm told.

I hate this. "Hippy crack" was always DMT when I was a yoot.

 

[nsno-chris]

That was one weird lad. Imagine citing P values when you have absolutely no idea what they are

Chat GTP has a lot to answer for

 

[nsno-chris]

To overcome the limitations of sample size and p-values in statistical analysis, you can consider the following strategies:

1. Increase Sample Size:
   • One of the most effective ways to address sample size limitations is to collect a larger sample of data. A larger sample size generally provides more precise estimates and can increase the statistical power of your analysis.
   • This can help reduce the risk of Type II errors (false negatives) and make it easier to detect smaller, yet practically significant, effects.
2. Effect Size Emphasis:
   • Instead of solely relying on p-values, focus on effect sizes. Effect sizes quantify the magnitude of the relationship or difference in your data, making it easier to assess the practical significance of your findings.
   • Even with a small sample size, a large effect size can still be meaningful.
3. Bayesian Analysis:
   • Consider using Bayesian statistical methods, which incorporate prior knowledge and allow for more flexible modeling. Bayesian analyses can provide more robust results with smaller sample sizes.
   • Bayesian credible intervals can also be used to complement p-values, providing a range of plausible parameter values.
4. Replication:
   • Replicate your study with independent samples or in different settings. Replication studies can help validate your findings and increase confidence in the results.
5. Meta-Analysis:
   • If possible, combine your study with others through meta-analysis. This can increase the effective sample size and provide a more comprehensive view of the research question.
6. Adjust Significance Threshold:
   • Consider adjusting the significance threshold (alpha level) if necessary. A more stringent threshold (e.g., 0.01) can reduce the likelihood of false positives (Type I errors) but may increase the risk of false negatives (Type II errors).
7. Use Confidence Intervals:
   • In addition to p-values, report confidence intervals for your estimates. Confidence intervals provide a range of plausible values, giving a sense of the precision of your results.
8. Robust Statistics:
   • Employ robust statistical methods that are less sensitive to outliers or violations of assumptions, which can be particularly helpful when dealing with small samples.
9. Expert Consultation:
   • Seek advice from statisticians or experts in your field to ensure that your statistical methods are appropriate and that you are interpreting the results correctly.

Remember that statistical analysis is not solely about achieving significant p-values but about drawing meaningful and robust conclusions from your data. Combining multiple approaches and focusing on the practical significance of your findings can help mitigate the limitations associated with small sample sizes and p-values.

Hi mate,

At least try a little harder

 

[ChesterBlue]

Hi mate,

At least try a little harder

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I owe him an apology for claiming he should be googling “How to not be a bellend”. Turns out he should’ve been asking ChatGPT this.

 

[nsno-chris]

I owe him an apology for claiming he should be googling “How to not be a bellend”. Turns out he should’ve been asking ChatGPT this.

Soon as I read it I knew it AI

The bellend didn’t even bother to try and piece it together like he knew what he was talking about

Obviously too busy because he was meeting “woman” at “pub” for “pint”

 

[Alan Whittle]

That was one weird lad. Imagine citing P values when you have absolutely no idea what they are

He’ll have asked his imaginary woman if she knew about P.

 

[Hinchcliffe's Corner]

Hi mate,

At least try a little harder

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Ladies and gents, we have an execution already and it's only early.

 

[ChesterBlue]

Soon as I read it I knew it AI

The bellend didn’t even bother to try and piece it together like he knew what he was talking about

Obviously too busy because he was meeting “woman” at “pub” for “pint”

The woman was probably Siri on his phone

 

[ElGato]

The bits you point out about the nefarious exploiting the thick and angry for their own means is hugely accurate. Turkeys voting for Christmas.

Divide and conquer.

The culture wars are a fine example too. Get people squabbling about what words mean. In the background continue to sell off public assets and line the pockets of the wealthy. People get angry because they wonder why they can't get a place in a local school or have to wait for a GP appointment. Stoke the fires with something about men playing womens sports. Rinse and repeat

Sad to see

 

[chicoazul]

Divide and conquer.

The culture wars are a fine example too. Get people squabbling about what words mean. In the background continue to sell off public assets and line the pockets of the wealthy. People get angry because they wonder why they can't get a place in a local school or have to wait for a GP appointment. Stoke the fires with something about men playing womens sports. Rinse and repeat

Sad to see

Mail on head. They hit the jackpot with the Brexit formula and it’s just intensified from there. The weaponising of the disaffected and the thick. Hope someone comes along soon to change that, yet I don’t see them.