PSY 2106 Lecture Notes - Lecture 7: Central Limit Theorem, Sampling Distribution, Thought Experiment
14 Nov 2018
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Document Summary
The frequency of the range of scores in a population of large sample tends to fall along a bell-shaped curve. What is so important about the normal distribution: it commonly occurs in the environment, central limit theorem. The distribution of the means of many samples all put together (sampling distribution) will approximate a normal curve: necessary for many statistical tests. When we have plotted the data using histogram bars, each bar represents a certain number of scores. When we plot data using a curve, the area under that curve represents a certain percentage of scores. 100% of our data falls in the area under the curve. Knowing this, we can look at any point on the curve and estimate what percentage of scores fall above/below it. We often discuss this as a probability (p) How do we know the probability of values in the standard normal distribution.
