เทคนิคการทำข้อสอบ Error Identification ง่ายๆ
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WINDOWS 7 – Troubleshooting your Dell Laptop Battery in Windows 7
Learn how to identify and resolve the most common causes for the battery warning, \”Plugged in, but not charging\”.
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Power and Sample Size Calculation
Power and Sample Size Calculation
Motivation and Concepts of Power/Sample Calculation, Calculating Power and Sample Size Using Formula, Software, and Power Chart
Type I error vs Type II error
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In this lesson, we will learn about the errors that can be made in hypothesis testing. Type I error is when you reject a true null hypothesis and is the more serious error. It is also called ‘a false positive’. The probability of making this error is alpha – the level of significance. Since you, the researcher, choose the alpha, the responsibility for making this error lies solely on you.
Type II error is when you accept a false null hypothesis. The probability of making this error is denoted by beta. Beta depends mainly on sample size and population variance. So, if your topic is difficult to test due to hard sampling or has high variability, it is more likely to make this type of error. As you can imagine, if the data set is hard to test, it is not your fault, so Type II error is considered a smaller problem.
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NullHypothesis DataScience Statistics
Type I and Type II Error | Research Methodology Sociology | Booster Dose of Sociology
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นอกจากการดูหัวข้อนี้แล้ว คุณยังสามารถเข้าถึงบทวิจารณ์ดีๆ อื่นๆ อีกมากมายได้ที่นี่: ดูบทความเพิ่มเติมในหมวดหมู่MẸO HAY