Interesting identity arising from fractional factorial design of resolution III

In summary, the solutions to your equation are the Mersenne primes, and this can be shown using the generalized binomial theorem.
  • #1
kalish1
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I am learning about statistical design of experiments, and in the process of mathematically rigorizing the concepts behind fractional factorial designs of resolution III, I derived an interesting equation:

$$k = \sum_{i=1}^{3}{\lceil{\log_2{k}}\rceil \choose i},$$ for which the solutions $k$ are the Mersenne primes.

How can I show this? Is the above equation algebraic? Is it even solvable analytically?

I have crossposted this question here, without any replies yet: statistics - Interesting identity arising from fractional factorial design of resolution III - Mathematics Stack Exchange

Thanks!
 
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  • #2
The equation you have derived is an algebraic equation and it is solvable analytically. One way to show this is to use the generalized binomial theorem. This theorem states that for any natural number $n$ and real numbers $a_1, a_2, \dots, a_n$, the following holds:
$$\sum_{i=0}^n\binom{n}{i}a_i = (a_1 + a_2 + \dots + a_n)^n.$$
Applying this theorem to your equation yields:
$$k = \sum_{i=1}^{3}\binom{\lceil \log_2 k \rceil}{i} = (2^{\lceil \log_2 k \rceil})^3 = 8^{\lceil \log_2 k \rceil},$$
which has the solution $k=M_p$, where $M_p$ is a Mersenne prime.
 

1. What is a fractional factorial design of resolution III?

A fractional factorial design of resolution III is a type of experimental design used in statistical analysis to study the effects of multiple variables on a response variable. It is a reduced version of a full factorial design, where not all possible combinations of variables are tested. Resolution III means that the design allows for the main effects of all variables and some interactions to be estimated.

2. How is a fractional factorial design of resolution III different from other experimental designs?

A fractional factorial design of resolution III is different from other experimental designs, such as full factorial and fractional factorial designs of higher resolution, in that it requires fewer experimental runs. This makes it more efficient and cost-effective, but it also means that it may not be able to detect certain interactions between variables.

3. What is the purpose of using a fractional factorial design of resolution III?

The purpose of using a fractional factorial design of resolution III is to efficiently and effectively study the effects of multiple variables on a response variable. It allows for the identification of important main effects and some interactions between variables, while reducing the number of experimental runs needed compared to a full factorial design. This is useful for researchers who may have limited resources or time.

4. What are some potential limitations of a fractional factorial design of resolution III?

One potential limitation of using a fractional factorial design of resolution III is that it may not be able to detect certain interactions between variables. This is because some interactions may be confounded with other main effects or interactions. Additionally, the design may not be suitable for studying complex relationships between variables, as it only allows for a limited number of variables to be included in the analysis.

5. What are some examples of real-life applications of a fractional factorial design of resolution III?

A fractional factorial design of resolution III can be applied in various fields, such as in product development, quality control, and pharmaceutical research. For example, it can be used in the food industry to test the effects of different ingredients and cooking methods on the taste and texture of a product. In pharmaceutical research, it can be used to study the effects of different doses and combinations of drugs on patient outcomes.

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