Nursing Student
New Grad

02.03 Distributions

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  1. Distribution
    1. Bimodal distribution- When a data set is graphed and there are 2 clear, distinct peaks (often times a mixture of two normal distributions)
      1. Examples- diseases, restaurant peak hours, water/electricity usage, book prices
    2. UniformDistribution- when a data set is graphed and there is one distinct peak. (aka normal distribution.
      1. Human birth weight, blood pressure, IQ scores, Average height of NBA players

Video Transcript

Today we’re going to be talking about statistical distributions.

The definition of a distribution in stats is a function that shows the possible values in a data set and how often they occur. So for example. We could think about flipping a coin. We know there are two sides to a coin and so the odds of it being heads or tails should be 50:50. Unless the coin is not fair. So we could flip the coin the same say 50 to 100 times and keep track of what we get each time. We could then graph the values for heads and tails and see the distribution of these two variables.

Bimodal is a type of distribution that forms 2 distinct peaks These 2 peaks are oftentimes a mixture of two normal distributions within a data set. So, for example, certain diseases have been known to show two distinct peaks or patterns in age groups. Cases of Kaposi’s sarcoma for example. There is a peak in older males and younger males that have AIDS.  Utility usage has two peaks.. morning and after work. Book prices have two extremes until you separate paperback from a hardback.

Uniform distribution has one clear distinct peak. Examples of this is human birth weight..most successful, blood pressure and the average height of an NBA player. Numbers are tight here and do not stray from the mean much on average.

So, in summary, a distribution in statistics is a function that shows us possible values for a variable. Bimodal distributions have 2 distinct peak values and a uniform distribution is when there is only on distinct peak value for the variable.

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