Sociology 2205A/B Lecture Notes - Lecture 7: Decision Rule, Normal Distribution, Statistical Inference
4 Oct 2018
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Document Summary
Hypothesis testing is designed to detect significant differences: differences that did not occur by random chance. In the "one sample" case: we compare a random sample (from a large group) to a population. We compare a sample statistic to a population parameter to see if there is a significant difference. Representative: the sample has the same characteristics as the population. Samples drawn according to the rule of equal probability of selection. Every case in the population has the same chance of being selected for the sample therefore are likely to be representative. We can use the sampling distribution to calculate the parameter based on our sample statistic. The single more important concept in inferential statistics. Every application of inferential statistics involves 3 different distributions. Information from the sample is linked to the population via sampling distribution. The h0 always states there is "no significant difference"
