Part 2 02: Put (True) or (False). Write True or False for six questions from the following question. Write the reasons for correct answers, and correct any statement/answer if it is false 1. As the sample size increases, the variance of the estimator decreases. 2. The mean of a normal distribution is the mean of the sample. 3. As the sample size decreases, the estimators are less accuracy. 4. If an estimator is consistent, it is also unbiased. 5. An unbiased estimator is consistent only if the variance of the estimator converges to zero. 6. The sufficient statistic is used for discrete data, while the consistent statistic is used for continuous data. 7. Two estimators are consistent, are asymptotically unbiased.

Part 2 02: Put (True) or (False). Write True or False for six questions from the following question. Write the reasons for correct answers, and correct any statement/answer if it is false 1. As the sample size increases, the variance of the estimator decreases. 2. The mean of a normal distribution is the mean of the sample. 3. As the sample size decreases, the estimators are less accuracy. 4. If an estimator is consistent, it is also unbiased. 5. An unbiased estimator is consistent only if the variance of the estimator converges to zero. 6. The sufficient statistic is used for discrete data, while the consistent statistic is used for continuous data. 7. Two estimators are consistent, are asymptotically unbiased.

Name: Part 2Q2: Put (True) or (False). Write True or False for six question
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Description: Part 2Q2: Put (True) or (False). Write True or False for six questions from the following question.Write the reasons for correct answers, and correct any statement/answer if it is false1. As the sample size increases, the variance of the estimator d

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Types of Bias

Statistics is the study of data collection, organization, analysis, interpretation, and presentation. Statistical bias is a characteristic of a statistical technique or its findings in which the expected value deviates from the actual root quantitative parameter being estimated. According to the actual definition of bias, it refers to the tendency of a statistic to overestimate or underestimate a parameter.

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