Given the following information:My confidence intervals: 90% confidence interval = (2.33, 2.56), and 99% confidence interval = (2.26, 2.63)My peer's confidence intervals: 90% confidence interval at ( 2.37 , 2.61 ) and 99% confidence interval at ( 2.31 , 2.67).How do their confidence intervals compare with yours?If the population standard deviation is unknown and the sample size is not sufficiently large, would you still use the Normal distribution to calculate these confidence intervals, or would you choose another distribution? If the latter, which distribution would you choose?

In statistics, confidence interval is the range in which one can be confident regarding a population…

Answered: Given the following information: My…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.4: Distributions Of Data

Problem 19PFA

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Given the following information:

My confidence intervals: 90% confidence interval = (2.33, 2.56), and 99% confidence interval = (2.26, 2.63)

My peer's confidence intervals: 90% confidence interval at ( 2.37 , 2.61 ) and 99% confidence interval at ( 2.31 , 2.67).

How do their confidence intervals compare with yours?
If the population standard deviation is unknown and the sample size is not sufficiently large, would you still use the Normal distribution to calculate these confidence intervals, or would you choose another distribution? If the latter, which distribution would you choose?

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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