Find the rejected region in the problem of a biased die - Hypothesis

  • Thread starter chwala
  • Start date
In summary, the conversation discusses the calculation of ##P(X≥10)## and ##P(X≥11)## using the method of subtracting from 1 and the steps involved in this approach. The questioner also asks if there is a simpler way to calculate these probabilities and seeks clarification on whether this method is correct. The response confirms that this is the correct approach and acknowledges that it may involve a lot of computation work.
  • #1
chwala
Gold Member
2,746
387
Homework Statement
Kindly see attached question and mark scheme guide
Relevant Equations
##Bin (n,p)##
Consider the question below:

1626846377308.png


this (below) is the mark scheme for the problem, there were different methods given in the mark scheme but i was interested on this one only...

1626846432252.png


Now onto my question, How did they calculate ##P(X≥10)##=##1-P(X≤9)##=##0.055##...?

In attempting to understand the question i went ahead and looked at a similar problem (attached below); i.e

1626846784214.png


and i could see from my analysis that, the highlighted value could have been found using the steps below:
##P(x≥4)=1- [ P(x=0) +P(x=1)+P(x=2)+P(x=3)]##
=## 1- [0.1615+0.3230+0.2907+0.1550]##
=##1-0.9302##
=##0.0698##
ok is this correct? if so going back to our problem, do we use the same approach? or there is a shorter way...
This is the only part that i need clarity. I should be able to come to the deduction on whether to reject or accept null hypothesis.
 
Last edited:
  • Like
Likes Delta2
Physics news on Phys.org
  • #2
Yes, this is the way to compute it.
 
  • #3
Orodruin said:
Yes, this is the way to compute it.
Thanks, implying that a student would have a lot of computation work to do (with calculator) to realize ##P(X≥10)## and ##P(X≥11)##... and then come to some conclusion... Phew!
 

FAQ: Find the rejected region in the problem of a biased die - Hypothesis

What is the problem of a biased die?

The problem of a biased die refers to the situation where a die is not equally likely to land on each of its sides. This can be due to manufacturing defects or intentional manipulation.

What is a hypothesis in this context?

A hypothesis is a proposed explanation for the biased die problem. It is a statement that can be tested and potentially proven or disproven through experimentation and data analysis.

How do you determine the rejected region in this problem?

The rejected region in this problem is determined by setting a significance level, typically denoted as alpha (α), which represents the maximum probability of incorrectly rejecting the null hypothesis (i.e. concluding that the die is biased when it is actually fair). The rejected region is then any outcome that falls below this significance level.

What is the null hypothesis in this problem?

The null hypothesis in this problem is that the die is fair and each side has an equal probability of landing face up. This is the default assumption and must be disproven in order to conclude that the die is biased.

How can you test the hypothesis in this problem?

The hypothesis can be tested by rolling the die a sufficient number of times and collecting data on the outcomes. This data can then be analyzed using statistical methods to determine if there is a significant deviation from the expected probabilities for each side. Additionally, experiments can be conducted with multiple dice to compare the results and strengthen the validity of the findings.

Back
Top