# PSYC 241 Lecture Notes - Lecture 3: Normal Distribution, Level Of Measurement, Central Tendency

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For unlimited access to Class Notes, a Class+ subscription is required. Lesson 3: Central Tendency
Central Tendency
Goal of Descriptive Statistics
To organize and summarize large groups of data
We want a handful of numbers that summarize a lot of numbers (we will also
use these measures for inferential stats as well)
Measures of Central Tendency
One number that summarizes all scores as an average
Arithmetic Mean:
Sum data, divide by number of scores
Mean =
Notation (symbols) for the mean
Population
µ =
Sample
∑x/n
Characteristics of the mean
Every time we add or subtract a score, we must recalculate the mean
If you +/- a score, the numerator and denominator both change
Transformation: smar mathematical operation to every score; just do the same to the
mean (used for inferential stats).
The mean is always our preferred measure of central tendency. Why?
Takes every score into account
Has a formula
Can easily transform scores
Median
No formal symbol
Median = (n + 1)/2
Middle score
Exactly in the middle of distribution
Same number above and below
To calculate
Put scores in ascending order
Find score that's right in the middle
Very important for skewed distributions
Mode
For categorical, nominal data
Most frequently occurring category or score
Can be determined for any scale of measurement
Distributions
Normal distribution
These three numbers are the same
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