How Do You Calculate Type 1 Error And Type 2 Error Probabilities?

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AnswerQuestion Answers for Class 12Class 12 BiologyClass 12 ChemistryClass 12 EnglishClass 12 MathsClass 12 PhysicsClass 12 Social ScienceClass 12 Business StudiesClass 12 EconomicsQuestion Answers for Class 11Class 11 EconomicsClass 11 Computer ScienceClass 11 BiologyClass 11 ChemistryClass 11 EnglishClass 11 MathsClass 11 PhysicsClass 11 Social ScienceClass 11 AccountancyClass 11 Business StudiesQuestion Answers for Class 10Class 10 ScienceClass 10 EnglishClass 10 MathsClass 10 Social ScienceClass 10 General KnowledgeQuestion Answers for Class 9Class 9 General KnowledgeClass 9 ScienceClass 9 EnglishClass 9 MathsClass 9 Social ScienceQuestion Answers for Class 8Class 8 ScienceClass 8 EnglishClass 8 MathsClass 8 Social ScienceQuestion Answers for Class 7Class 7 ScienceClass 7 EnglishClass 7 MathsClass 7 Social ScienceQuestion Answers for Class 6Class 6 ScienceClass 6 EnglishClass 6 MathsClass 6 Social ScienceQuestion Answers for Class 5Class 5 ScienceClass 5 EnglishClass 5 MathsClass 5 Social ScienceQuestion Answers for Class 4Class 4 ScienceClass 4 EnglishClass 4 MathsHow do you calculate type 1 error and type 2 error probabilities?AnswerVerified543.6k+ viewsHint: We first express the concept of type 1 error and type 2 error probabilities. Then we state the theorems for calculating the probabilities.Complete step by step solution:When the null hypothesis $\left( {{H}_{0}}:\mu ={{\mu }_{0}} \right)$ is true and we reject it, we make a type 1 error. The probability of making a type I error is $\alpha $, which is the level of significance you set for your hypothesis test. An $\alpha $ of 0.05 indicates that we are willing to accept a 5% chance that we are wrong when you reject the null hypothesis. When the null hypothesis is false and we fail to reject it, you make a type 2 error. The probability of making a type II error is $\beta $, which depends on the power of the testThe formulas for finding the probabilities areType 1: \[P\left( \text{rejecting }{{H}_{0}}|{{H}_{0}}\text{ true} \right)\] and Type 2: \[P\left( \text{accepting }{{H}_{0}}|{{H}_{0}}\text{ false} \right)\].Note: To lower this risk in type 1, we must use a lower value for $\alpha $. However, using a lower value for alpha means that we will be less likely to detect a true difference if one really exists. We can decrease your risk of committing a type 2 error by ensuring our test has enough power. We can do this by ensuring your sample size is large enough to detect a practical difference when one truly exists.Recently Updated PagesMaster Class 11 Business Studies: Engaging Questions & Answers for SuccessMaster Class 11 English: Engaging Questions & Answers for SuccessMaster Class 11 Computer Science: Engaging Questions & Answers for SuccessMaster Class 11 Social Science: Engaging Questions & Answers for SuccessMaster Class 11 Maths: Engaging Questions & Answers for SuccessMaster Class 11 Biology: Engaging Questions & Answers for SuccessMaster Class 11 Business Studies: Engaging Questions & Answers for SuccessMaster Class 11 English: Engaging Questions & Answers for SuccessMaster Class 11 Computer Science: Engaging Questions & Answers for SuccessMaster Class 11 Social Science: Engaging Questions & Answers for SuccessMaster Class 11 Maths: Engaging Questions & Answers for SuccessMaster Class 11 Biology: Engaging Questions & Answers for Success

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