Hi, I would appreciate if you could help me with the following question please. ### Statistical Confidence Intervals**Question:**A 95% confidence interval for $ p_1 - p_2 $ is calculated to be (0.1823, 0.3001). If the level of confidence is now decreased to 90%, what happens to the confidence interval?**Options:**- a. Unknown- b. It increases in size- c. It decreases in size- d. It remains the same**Explanation:**When the level of confidence is decreased (from 95% to 90% in this case), the confidence interval generally becomes narrower. This means that the confidence interval decreases in size because we are accepting a higher level of uncertainty for a narrower range of values.#### Answer:c. It decreases in sizeUnderstanding this concept is crucial for interpreting confidence intervals and making informed decisions based on statistical data analysis.

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Description: Hi, I would appreciate if you could help me with the following question please. ### Statistical Confidence Intervals**Question:**A 95% confidence interval for $ p_1 - p_2 $ is calculated to be (0.1823, 0.3001). If the level of confidence is now dec

Given that a 95% confidence interval for p1-p2 is calculated to be (0.1823,0.3001). if the level of…

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A 95% confidence interval for p, - P2 is calculated to be (0.1823, 0.3001). If the level of confidence is now decreased to 90%, what happens to the confidence interval? O a. Unknown b. It increases in size c. It decreases in size o d. It remains the same

A 95% confidence interval for p, - P2 is calculated to be (0.1823, 0.3001). If the level of confidence is now decreased to 90%, what happens to the confidence interval? O a. Unknown b. It increases in size c. It decreases in size o d. It remains the same

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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