On page 289 there is a box titled “Premises need for a good generalization”:
- The sample is representative
- The sample is big enough
- The sample is studied well
There should also be a small margin of error for the population sample (about +/-2%) and a larger confidence level for the population sample (about +/-95%). Both give strength to the generalization given and have more reason for it to be accepted.
Variation is also important in a population. If the number of people who own motorcycles is being tested for the state of California, the sample should be testing a more or less equal amount of men and women.
Your blog about generalizing is very good. I think you definitely grasped the important concepts from the chapter. I often read things where they give a generalization about the population and I don’t know if it is actually true. At the same time I know I have probably made comments generalizing about a certain population even if I am not sure or don’t have an accurate sample to base my reasoning off of. I think it is important to have a pretty even mix of people so that wide spectrums of opinions are being taken into account. Although a lot of generalizations are made I think that not many of them you hear in random conversations with friends or on advertisements are good.
ReplyDeleteNicely written Catalina. As usual, a very good post! Here's why... Well I have not yet read chapter 14 since I have been busy with tutoring and studying for finals. Even with out reading this chapter, I at least have an idea what generalizing is. The only part I missed was how to correct it. This topic is interesting because everyone has generalized a race, sex, or group of people. For example, we generalize gangs as dangerous. Yes from experience they can be, but I disagree that all gangs are like that. I've personally met a gang that turned away from violence to help people. As ironic as it sounds,it basically contradicts the generalization. That's when the percent error applies.
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