Question 4 After some time has passed, all of the chickens lay full-sized eggs. (When chickens first start laying, many of their eggs are small.) So, the mean weight goes up to 24 ounces. At the same time, the variation decreases, so the standard deviation goes down to 2 ounces. Mark off a normal distribution with the numbers for the mean and each deviation by labeling the values for A, B, C, D, E, F, and G in the table. Value A B C D E F G

Question 4 After some time has passed, all of the chickens lay full-sized eggs. (When chickens first start laying, many of their eggs are small.) So, the mean weight goes up to 24 ounces. At the same time, the variation decreases, so the standard deviation goes down to 2 ounces. Mark off a normal distribution with the numbers for the mean and each deviation by labeling the values for A, B, C, D, E, F, and G in the table. Value A B C D E F G

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

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section: Chapter Questions

Problem 19SGR

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Question 4

After some time has passed, all of the chickens lay full-sized eggs. (When chickens first start laying, many of their eggs are small.) So, the mean weight goes up to 24 ounces. At the same time, the variation decreases, so the standard deviation goes down to 2 ounces.

Mark off a normal distribution with the numbers for the mean and each deviation by labeling the values for A, B, C, D, E, F, and G in the table.

	Value
A
B
C
D
E
F
G

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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