A study shows in a certain school that the average number of hours a student answers his/her module in a day is 26.8 hours with a standard deviation of 5.57. Assuming that the data are normally distributed, d) Find the probability that the number of hours spent by a student in answering his/her modules is between 19 hours and 28 hours. e) If there were 2,780 students in that school, how many students spent between 15 and 41 hours in answering his/her modules.

A study shows in a certain school that the average number of hours a student answers his/her module in a day is 26.8 hours with a standard deviation of 5.57. Assuming that the data are normally distributed, d) Find the probability that the number of hours spent by a student in answering his/her modules is between 19 hours and 28 hours. e) If there were 2,780 students in that school, how many students spent between 15 and 41 hours in answering his/her modules.

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Question

d) Find the probability that the number of hours spent by a student in answering his/her modules is between 19 hours and 28 hours.

e) If there were 2,780 students in that school, how many students spent between 15 and 41 hours in answering his/her modules.

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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