Class notes

Standard Deviation (Week 2 Notes)

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Course
Psyc 101

Institution
University Of British Columbia (UBC )

The Standard Deviation Notes provide a comprehensive understanding of one of the key statistical measures in data analysis. Gain insights into the concept and calculation of standard deviation, which measures the dispersion or variability of a dataset. Explore how standard deviation is used to asse...

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Uploaded on May 11, 2023
Number of pages 2
Written in 2020/2021
Type Class notes
Professor(s) Eva zysk
Contains Standard deviation

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Standard Deviation Notes

- Standard deviation
calculated with the mean
can tell you how spread
out data is.
- Can be calculated with
spreadsheet, calculator,
or math equation.
1. Calculate mean
2. Subtract the mean
from each data point
3. Square each
difference
4. Calculate the mean of
the squared
differences
5. Take the square root.
- Lower case sigma stands for standard deviation of a population. Upper case sigma
tells us to calculate the sum for each instance. X is each data point. X bar is the
mean of the data points. And n is the number of data points.

The Normal distribution
- Data from a population or sample
- Parameter: a number that describes data from a population
- Statistic: a number that describes data from a sample
- Mean + Standard Deviation.

Sample Population
Mean -Over X Greek letter 
Standard s Greek letter 
Deviation
Type Statistic Parameter
Graph Characterizes the spread of the Characterizes the position
normal distribution. Larger the of the normal distribution.
standard deviation (), flatter the Curve always follows the
curve will be, smaller the standard mean ()
deviation (), taller the curve will
be.

- A special type of bell curve shaped  bell/normal curve
- Tendency for data to cluster around central value (mean)
- Weight, height, volume etc.
- Exam scores follow normal distribution.
- The normal distribution is unimodal (single peak)
- The normal curve is symmetric about its mean (middle is tallest)
- The parameters  and completely  characterize the normal distribution
- X ~ N (, ) (variable x has a normal distribution with a mean miu and standard
deviation of sigma)

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