2^k factorial experiment design

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The discussion centers on the concept of 2^k factorial experiment design, specifically with two factors (a and b). In this design, k represents the number of factors, and each factor has two levels, resulting in 2^k combinations—in this case, four combinations. The term "replicates" refers to the number of times each combination is tested to ensure reliability and accuracy of results. In this scenario, three observations are made for each of the four combinations, meaning the experiment is repeated three times for each combination to measure the yield consistently. The conversation also hints at the implications of increasing k to three, suggesting that the number of combinations and the corresponding replicates would increase accordingly, maintaining the same principle of repeated trials for each combination.
physea
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Hello!

In this webpage:
https://onlinecourses.science.psu.edu/stat503/node/35

it describes the 2^k factorial experiment design. I understand that k is the number of factors that we are investigating (in this case two, a and b), 2 are the levels of each factor (+/-) and 2^k=4 is the number of the all possible combinations of these factors (null, a, b, ab).

However, I don't understand what he means with "You can see that we have 3 observations at each of 4 = 2k combinations for k = 2. So we have n = 3 replicates." What are these three observations for each combination and why they are called replicates?

What happens in k=3 etc situations with these replicates?

thanks!
 
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The replicates are simply the number of times the experiment was performed. For each of the ##2^k## combinations, the reaction was carried out 3 times and the yield measured each time.
 
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