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Ch6_Normal Distribution &amp; Probability

# Ch6_Normal Distribution &amp; Probability - Chapter 6...

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Chapter 6 The Normal Distribution, Probability and Standard Scores

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Normal Distribution Normal distribution is crucial theoretical mathematical distribution used in statistics. Also call “Gaussian distribution,” Bell curve.
The Normal Curve μ -3 σ -2 -1 +1 +2 +3 .3413 .3413 .1359 .1359 .0215 .0215

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The Normal Curve Characteristics of a normal distribution: smooth symmetrical bell-shaped unimodal asymptotic (tails never touch base line) continuous
Why Normal Curve Is Important? Many of the variables measured in science research have distributions that quite closely approximate the normal curve. Many of the statistics used in summarizing data have sampling distributions that become normal with increasing sample size.

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Equation of the Normal Curve : The Normal Curve is a bell shaped curve that is described by the following equation : where, Y = frequency of a given value of X X = any score in the distribution 2200 μ = mean of the distribution 2200 σ = standard deviation of the distribution N = total frequency of the distribution 2200 π = a constant of 3.1416 e = a constant of 2.7183

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Horizontal Axis: The horizontal axis gives you the values of the variable of interest in a  particular research project. It might be  values of IQ or blood pressure or substance use behavior  score.
Vertical Axis: The height of the Normal Probability curve is

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Ch6_Normal Distribution &amp; Probability - Chapter 6...

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