Yh, the video was insightful and will be expecting it to be re-uploaded soon. If you can touch on calculating the effect size in the software (G*Power), that will be great. Clicking on the "Determine =>" tab opens up a new tab which allows you to input parameters to calculate the effect size
Let me just answer you here. In summary, not changing the alpha value from 0.05 to 0.025 in a two-tailed analysis can lead to an increased risk of Type I errors, less stringent criteria for significance, potential misinterpretation of results, and a compromise in the validity of the research findings. Adjusting alpha levels appropriately is crucial to ensure the reliability and accuracy of statistical hypothesis testing.
Yh, the video was insightful and will be expecting it to be re-uploaded soon.
If you can touch on calculating the effect size in the software (G*Power), that will be great. Clicking on the "Determine =>" tab opens up a new tab which allows you to input parameters to calculate the effect size
Yh, I will certainly do that. Your previous comment was beneficial. Thanks for that.
What will be the consequences of not changing the alpha value from 0.05 to 0.025 even when you are doing a two-tailed anaysis?
I will demonstrate that in my new video.
Let me just answer you here. In summary, not changing the alpha value from 0.05 to 0.025 in a two-tailed analysis can lead to an increased risk of Type I errors, less stringent criteria for significance, potential misinterpretation of results, and a compromise in the validity of the research findings. Adjusting alpha levels appropriately is crucial to ensure the reliability and accuracy of statistical hypothesis testing.