Calculating N of Possible Answers on Filtered Tests

In summary, the conversation discusses a formula for determining the number of possible answer paths on a filtered test format, where a correct answer is required to proceed to the next question. The formula involves calculating the number of passing and failing options for each question and using a specific notation to represent the total number of answer choices. The formula provided in the conversation seems to be accurate, but suggestions for making it more efficient are given.
  • #1
psychometriko
3
0
Hopefully I'm posting this to the appropriate section. I am trying to figure out a formula for describing the number of possible answer "paths" that may be taken by an individual who is administered a filtered test format. In the filtered test format, the individual must select a passing response to item j in order to proceed to item j + 1. If the individual selects a failing option, the test is over. My question is, given that each of the items on the test can have different numbers of passing and failing options (e.g., item j might have two passing options and three failing options, item j + 1 might have one passing option and two failing options), how can I even begin to figure out how to put this down mathematically on paper? My math background is rather weak, so I'm not really even sure where to start. Any help would be much appreciated!
 
Physics news on Phys.org
  • #2


You can calculate it step by step: For the first question, there are n1 answers, c1 of them are correct. Therefore, you have n1-c1 ways to fail the test, and c1 ways to proceed.

The second question has n2 answers, c2 of them are correct. For each way to reach this question, you have nn-cn ways to fail the test, and c2 ways to proceed.

Does that help?
You can get a general formula using this approach, too.
 
  • #3


Thanks for the reply. After I posted this I actually worked out a formula, but it's really clunky and I couldn't really say how I derived it. Here's what I have (by the way I'm uploading a JPG for this because I know if I tried to type it in I would screw it up real nice).

Explanation of notation:
M = total number of answer possibilities (number of "paths")
k = 1,...,K is the number of items on the test
V is the total number of answer choices on item k
VkP is the number of passing answers on item k
VkF is the number of failing answers on item k
Hence, VK is the total number of answer choices on the last (Kth) item on the test, and V1F is the number of failing answers on the first item (k = 1) on the test. (And in the last term in the formula, n is used as an arbitrary index.)

Any advice for making this prettier/more efficient?

Thanks!


mfb said:
You can calculate it step by step: For the first question, there are n1 answers, c1 of them are correct. Therefore, you have n1-c1 ways to fail the test, and c1 ways to proceed.

The second question has n2 answers, c2 of them are correct. For each way to reach this question, you have nn-cn ways to fail the test, and c2 ways to proceed.

Does that help?
You can get a general formula using this approach, too.
 

Attachments

  • formula.jpg
    formula.jpg
    6.3 KB · Views: 418
  • #4


I did not check all indices, but the formula looks good. I think you can include V_1^F in the last expression, using the convention that an empty product (from n=1 to n=0) is 1.

In the same way, you can include the case "n-1 correct answers and failed at the last one" there, which simplifies the first part a bit.
 
  • #5


Great, thanks for the tips!

mfb said:
I did not check all indices, but the formula looks good. I think you can include V_1^F in the last expression, using the convention that an empty product (from n=1 to n=0) is 1.

In the same way, you can include the case "n-1 correct answers and failed at the last one" there, which simplifies the first part a bit.
 

Related to Calculating N of Possible Answers on Filtered Tests

1. How do you calculate the number of possible answers on filtered tests?

To calculate the number of possible answers on filtered tests, you first need to determine the total number of questions on the test. Then, you need to identify the number of possible answers for each question. Finally, multiply the number of questions by the number of possible answers for each question to get the total number of possible answers on the filtered test.

2. Why is it important to calculate the number of possible answers on filtered tests?

Calculating the number of possible answers on filtered tests is important because it helps to determine the difficulty level of the test. It also allows for better test preparation and analysis of results.

3. How does the number of possible answers affect the validity of a filtered test?

The number of possible answers can affect the validity of a filtered test as it can impact the difficulty level and the accuracy of the test. If there are too few possible answers, the test may be too easy and not accurately assess the knowledge and skills of the test-taker. On the other hand, if there are too many possible answers, the test may be too difficult and not accurately reflect the test-taker's abilities.

4. Are there any limitations to calculating the number of possible answers on filtered tests?

Yes, there are limitations to calculating the number of possible answers on filtered tests. This method does not take into account the complexity or difficulty level of each question, which can also affect the overall difficulty of the test. Additionally, it may not account for the possibility of multiple correct answers for a single question.

5. Can the number of possible answers on filtered tests be manipulated to achieve a desired outcome?

It is not recommended to manipulate the number of possible answers on filtered tests to achieve a desired outcome. This can compromise the validity and reliability of the test and may not accurately assess the test-taker's knowledge and skills. It is important to create tests with a fair and balanced number of possible answers to accurately measure the test-taker's abilities.

Similar threads

  • Set Theory, Logic, Probability, Statistics
2
Replies
39
Views
4K
Replies
20
Views
650
  • Set Theory, Logic, Probability, Statistics
Replies
4
Views
586
  • Set Theory, Logic, Probability, Statistics
7
Replies
212
Views
12K
Replies
9
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
7
Views
1K
Replies
80
Views
4K
  • Set Theory, Logic, Probability, Statistics
Replies
4
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
10
Views
554
Replies
5
Views
2K
Back
Top