Assuming that student incomes from employment in industry during the day are normally distributed with a mean income of $30,000 and a standard deviation of $3,000. a) What is the probability that a randomly selected student earns more than $30,000? b) What’s the probability that a randomly selected student earns between $27,000 and $33,000? c) What’s the probability that the average income of a sample of 30 students is less than $28000?

Assuming that student incomes from employment in industry during the day are normally distributed with a mean income of $30,000 and a standard deviation of $3,000. a) What is the probability that a randomly selected student earns more than $30,000? b) What’s the probability that a randomly selected student earns between $27,000 and $33,000? c) What’s the probability that the average income of a sample of 30 students is less than $28000?

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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Concept explainers

Estimation

A new framework of data analysis where the new statistical methods are used for interpreting the results and analyzing the data is known as estimation in statistics.

Question

Assuming that student incomes from employment in industry during the day are normally distributed with a mean income of

$30,000 and a standard deviation of $3,000.

a) What is the probability that a randomly selected student earns more than $30,000?

b) What’s the probability that a randomly selected student earns between $27,000 and $33,000?

c) What’s the probability that the average income of a sample of 30 students is less than $28000?

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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