In Lesson 2, 40 volunteers were randomly assigned to one of 4 experimental conditions, but the result was that only 7 participants ended up in Condition 1 — half the number that ended up in Condition 2. This kind of result is common in random assignment, just as tossing a coin 20 times usually leads to a different result than exactly 10 heads and 10 tails.

Unfortunately, large differences in sample size can interfere with certain statistical tests. One way around this problem is to use a "blocked design" in which participants are randomly assigned within a block of trials. In the drug experiment from Lesson 2, for example, we could divide the 40 volunteers into 10 blocks of 4 participants and then randomly assign each person within a block to one of the four experimental conditions, such as:

Block 1:

- Participant 001: Condition 3
- Participant 002: Condition 1
- Participant 003: Condition 4
- Participant 004: Condition 2

Block 2:

- Participant 005: Condition 4
- Participant 006: Condition 2
- Participant 007: Condition 1
- Participant 008: Condition 3

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To generate random numbers for this kind of blocked design, you would fill out the Randomizer form for 10 sets of 4 unique, unsorted numbers with a range from 1 to 4 (representing the four conditions). For this example, we will also use the "Place Markers Across" viewing option to simplify interpretation of the results.