Example: Do Babies Prefer Helpers?<\/b><\/h3>\r\n
In a classic study published in Nature<\/i> (Hamlin, Wynn, & Bloom, 2007), researchers asked a fascinating question:<\/p>\r\n In one version of the experiment, 10-month-old babies watched a simple puppet show:<\/p>\r\n After several repetitions, the infants were shown both toys\u2014the helper<\/span> and the hinderer<\/span>\u2014and invited to choose one to play with.[footnote]Hamlin, J. K., Wynn, K., Bloom, P., & Mahajan, N. (2011). How infants and toddlers react to antisocial others. Proceedings of the National Academy of Sciences<\/em>, 108(50), 19931-19936. https:\/\/doi.org\/10.1073\/pnas.1110306108[\/footnote]<\/p>\r\n\r\n[caption id=\"attachment_169\" align=\"aligncenter\" width=\"1024\"] Of the 16 infants<\/span> who made a clear choice, 14 picked the helper toy<\/span>.<\/p>\r\n That seems like a strong preference\u2014but scientists must rule out other explanations before drawing conclusions.<\/p>\r\n The researchers controlled for:<\/p>\r\n After accounting for these factors, one question remained: Could the result still be due to random chance<\/span>?<\/p>\r\n<\/section>\r\n Even if all infants had no real preference<\/span>, we wouldn\u2019t expect exactly half to pick each toy every time. Random variation happens naturally.<\/p>\r\n For instance, if each baby\u2019s choice were like flipping a coin<\/span>\u201450% chance helper, 50% chance hinderer\u2014we might sometimes get 9 \u201chelper\u201d choices out of 16, sometimes 7, sometimes 11. But getting 14 out of 16<\/span> \u201chelper\u201d choices would be very unusual if the choices were purely random.<\/p>\r\n Getting 14 (or more) heads in 16 tosses is about as likely as tossing a coin and getting 9 heads in a row. This probability is referred to as a p-value<\/strong>. The p-value represents the likelihood that experimental results happen by chance.\u00a0<\/p>\r\n Psychologists typically use a standard of p < .05<\/b><\/span> (less than a 5% chance that the result happened randomly) to decide whether results are statistically significant.<\/em><\/strong><\/p>\r\n If the probability of getting the observed result by chance is smaller than 5%, researchers conclude that the effect is unlikely to be random<\/span>. Because p = 0.0021<\/span> is far smaller than .05, the researchers concluded that infants showed a genuine preference for the helper toy<\/span>. In other words, the babies\u2019 choices likely reflect something real about social evaluation\u2014not luck.<\/p>\r\n Statistical significance doesn\u2019t \u201cprove\u201d a theory\u2014it simply tells us that the pattern we observed is very unlikely to have happened by accident. Even when we find patterns in data, often there is still uncertainty in various aspects of the data. For example, there may be potential for measurement errors (even your own body temperature can fluctuate by almost 1 \u00b0F over the course of the day), or we may need to make generalizations about the entire population based on a small snapshot of data. In such cases, we use statistics to help us understand the probability that our data is telling the right story.<\/p>\n In a classic study published in Nature<\/i> (Hamlin, Wynn, & Bloom, 2007), researchers asked a fascinating question:<\/p>\n Can infants judge others based on helpful or harmful behavior?<\/p><\/blockquote>\n In one version of the experiment, 10-month-old babies watched a simple puppet show:<\/p>\nCan infants judge others based on helpful or harmful behavior?<\/blockquote>\r\n
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Figure 1<\/strong>. In the research study, babies were shown a character trying to climb up a hill. In this case, the red circle was trying to climb the hill and the blue square helped it up, while the yellow triangle pushed it down.[\/caption]\r\n\r\n\r\n\t
Understanding Randomness in Research<\/b><\/h3>\r\n
P-value<\/h3>\r\n
What Does \u201cStatistically Significant\u201d Mean?<\/b><\/h3>\r\n
\r\nResearchers still need to replicate studies and consider effect size, design quality, and potential biases before drawing firm conclusions.<\/p>\r\nStatistical Significance and P-Values<\/h2>\n
Example: Do Babies Prefer Helpers?<\/b><\/h3>\n
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