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invest_3ed.pdf

# In other words our analysis is going to assume the

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the infants are randomly guessing. In other words, our analysis is going to assume the researchers’ conjecture is wrong (for the moment) and that infants really are just blindly picking one toy or the other without any regard for whether it was the helper toy or the hinderer. (e) Suggest a method for carrying out this simulation of infants picking equally between the two toys. (f) Explain why looking at such “could have been” results will be useful to us. Discussion: We will call the assumption that these infants have no genuine preference between the toys the null model . Performing lots of repetitions under this model will enable us to see the pattern of results (number who choose the helper toy) when we know the infants have no preference . Examining this null distribution will in turn help us to determine how unusual it is to get 14 infants picking the helper toy where there is no genuine preference. If the answer is that that the result observed by the researchers (14 of 16 choosing the helper toy) would be very surprising for infants who had no real preference, then we would have strong evidence to conclude that infants really do prefer the helper. Why? Because otherwise, we would have to believe a very rare coincidence just happened to occur in this study. Summing up: An observed outcome that would rarely happen if a claim were true provides strong evidence that the claim is not true.

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Chance/Rossman, 2015 ISCAM III Investigation 1.1 22 Simulation (g) Flip a coin 16 times, representing the 16 infants in the study (one trial or repetition from this random process). Let a result of heads mean that the infant chooses the helper toy, tails for the hinderer toy. Tally the results below and count how many of the 16 chose the helper toy: “Could have been” distribution Heads (helper toy) Tails (hinderer toy) Total number of heads in 16 tosses: (h) Repeat this two more times. Keep track of how many infants, out of the 16, choose the helper. Record this number for all three of your repetitions (including the one from the previous question): Repetition # 1 2 3 Number of (simulated) infants who chose helper (i) Combine your simulation results for each repetition with your classmates on the scale below. Create a dotplot by placing a dot above the numerical result found by each person. (j) Did everyone get the same number of heads every time? What is an average or typical number of heads? Is this what you expected? Explain. (k) How is it looking so far is the actual study result (14 picking the helper toy) consistent with the outcomes that could have happened under the null model? Which explanation (1) or (2) do you think is more plausible based on this null distribution? Explain your reasoning.
Chance/Rossman, 2015 ISCAM III Investigation 1.1 23 We really need to simulate this hypothetical random selection process hundreds, preferably thousands of times. This would be very tedious and time- consuming with coins, so let’s turn to technology.

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