What is the probability of a cable having a breaking load greater than 6200 N?

  • Context: Undergrad 
  • Thread starter Thread starter rexxii
  • Start date Start date
  • Tags Tags
    Probability Value
Click For Summary

Discussion Overview

The discussion revolves around calculating the probability of a cable having a breaking load greater than 6200 N, based on a normal distribution with a specified mean and standard deviation. Participants are exploring the correct interpretation of z-scores and probability tables in the context of statistical analysis.

Discussion Character

  • Mathematical reasoning
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant calculates the z-value for a breaking load of 6200 N as 1.29 but expresses confusion about how to interpret this value in relation to the normal distribution.
  • Another participant points out that the probability statement derived from the z-table is incorrectly interpreted, clarifying that the table provides P(z < 1.290) = 0.9015, not P(z > 1.290).
  • A subsequent query asks whether the participant should read from the right-hand side of the z-table since the value is above the mean.
  • Another participant explains that the area under the curve to the left of z = 1.290 represents the cumulative probability, prompting questions about the total area under the curve and the area to the right of the z-value.
  • There is a challenge regarding the mixing of concepts between z-values and associated probabilities, with a suggestion to review relevant textbook material for better understanding.

Areas of Agreement / Disagreement

Participants express differing levels of understanding regarding the interpretation of z-scores and the use of probability tables. There is no consensus on the correct approach to calculating the desired probability, and confusion remains about the relationship between z-values and probabilities.

Contextual Notes

Participants have not fully resolved the mathematical steps involved in calculating the probability, including the correct interpretation of cumulative probabilities and areas under the normal distribution curve.

rexxii
Messages
11
Reaction score
0
TL;DR
Probability - z value - stats issue
Hi,

I'm working on a question now where I need to calculate the z value. which I have been able to but I'm calculating a value off the normal distribution that is on the left-hand side of the normal distribution curve and it needs to on the right side. As the value I'm looking into is higher than the mean!

I cannot figure out how I would turn this around. its only one independent event there's no replacement or other variables.

the question is:

A cable manufacturer tests the cables it produces to find the breaking load. Over many years this has been assumed to be normally distributed with a mean of 6000 Newtons and standard deviation of 155 Newtons. Calculate the probability that a single cable chosen at random, will have a breaking load greater than 6200 N. Z = 6200 -6000 /155 = 1.29

Then I've written a probability statement (P z>1.290) = P z>1.290)

read from the stats tables that it could be 0.9015.

Said the breaking load is 90.15%

I know this is incorrect please can you advise The probability that a randomly selected cable will have a breaking load greater breaking load than 6200 Newtons is 90%.
 
Last edited by a moderator:
Physics news on Phys.org
rexxii said:
Summary: Probability - z value - stats issue

Hi,

I'm working on a question now where I need to calculate the z value. which I have been able to but I'm calculating a value off the normal distribution that is on the left-hand side of the normal distribution curve and it needs to on the right side. As the value I'm looking into is higher than the mean!

I cannot figure out how I would turn this around. its only one independent event there's no replacement or other variables.

the question is:

A cable manufacturer tests the cables it produces to find the breaking load. Over many years this has been assumed to be normally distributed with a mean of 6000 Newtons and standard deviation of 155 Newtons. Calculate the probability that a single cable chosen at random, will have a breaking load greater than 6200 N. Z = 6200 -6000 /155 = 1.29

Then I've written a probability statement (P z>1.290) = P z>1.290)

read from the stats tables that it could be 0.9015.
You're reading the table wrong. The table is giving you P(z < 1.290) = 0.9015. So what would be the probability you want, P(z > 1.290)?
rexxii said:
Said the breaking load is 90.15%

I know this is incorrect please can you advise The probability that a randomly selected cable will have a breaking load greater breaking load than 6200 Newtons is 90%.
 
So i need to read from the RHS side? as it is above the mean? Would i still select that number or a different one of the table?
 
P(z < 1.290) = .9015, from the table. The number .9015 represents the area under the standard normal curve between ##z = -\infty## and z = 1.290. What is the total area under the curve? What's the area under the curve between z = 1.290 and ##z = +\infty##?
 
1.29 - 1 = 0.29 above the mean?
 
rexxii said:
1.29 - 1 = 0.29 above the mean?
No, and this doesn't make any sense -- you're mixing two unrelated things there: the z-value and the probability associated with a certain z-value.

Have you seen a graph of the standard normal curve? In the standard normal distribution, half of the area under the curve is to the left of the mean at z = 0, and the other half is to the right. What's the total area under the curve? How much of the area under the curve lies to the left of z = 1.29? How much of the area lies to the right of z = 1.29?

It would be a good idea to read the section in your textbook that has this problem. There's quite a bit you don't understand.
 

Similar threads

  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
Replies
2
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
Replies
8
Views
3K
Replies
7
Views
2K
  • · Replies 15 ·
Replies
15
Views
3K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K