BENEFITS OF DOCUMENT
DESCRIPTION
A set of PowerPoint slides related to calculating normal distribution probabilities using manual methods and through spreadsheet software.
The slides walk through a step-by-step method of calculating probabilities manually to give background so that when you use software to accomplish the same calculation you understand what is happening.
There are three major areas of shading possible under a normal curve:
1) Left shading problems (shade to the left of a number under the curve)
Example: mean 100, standard deviation of 10, what is the probability of less than 90?
2) Right shading problems (shade to the right of a number under the curve)
Example: mean 100, standard deviation of 10, what is the probability of greater than 110?
3) Between shading problems (shade between two numbers under the curve)
Example: mean 100, standard deviation of 10, what is the probability of between 90 and 110?
Left shading problems: 2 steps are reviewed. Calculate the z-score and lookup the probability in a reference table.
Right shading problems: 3 steps are reviewed. Same steps as left shading but subtract from 1 as a third step.
Between shading problems: 5 steps are reviewed. Calculate two z-scores. Lookup two values in the reference table. Subtract the lower value from the higher value.
The lecture has been used in many Statistics courses I have written and led as an instructor.
The second part of the presentation slides addresses how to calculate the same probabilities with Microsoft Excel functions.
Using the same recipe-like steps, but now using Microsoft Excel functions, you can see how to implement the calculations easily using software.
Assumptions for the manual method are that you have access to a normal distribution table (could be looked up online).
Assumptions for the Microsoft Excel functions are that you have access to Microsoft Excel software.
Practice slides give examples on how to perform the work both manually and through software.
Microsoft Excel NORMDIST, NORMINV, NORMSDIST, and NORMSINV functions are explained with examples.
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Source: Normal Distribution Lecture PowerPoint (PPTX) Presentation, jsniderfamily
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