PSYC 2300 Lecture Notes - Lecture 11: Squared Deviations From The Mean, Standard Deviation

17 views2 pages
30 Aug 2018
1. Overview
a. Variability can be defined in several ways
i. Numerical difference between scores (quantitative distance)
ii. Distance of a score from mean
b. Purposes of variability
i. Describe distribution
ii. Measures how well an individual score represents distribution
c. 3 measures
i. Range
ii. Standard deviation
iii. Variance
2. Range
a. Smallest to largest
b. Difference between maximum and minimum
c. If using continuous data
i.  
d. Crude and unreliable measure
i. Not resistant to extremes
ii. Based on 2 scores, not all data
e. IQE is measure of range/difference between upper & lower quartiles
3. Standard deviation and variance
a. Standard deviationmost common and most important
b. Standard distance from mean
c. Tells us if the scores are clustered around mean or widely scattered
d. Variance is a companion measure
e. Calculating standard deviation and variance
i. Determine deviation (distances from mean)
1. Deviation score:
a. Do this for each score
ii. Calculate average deviation
iii. Get rid of +/- in deviations
1. Square each deviation
2. Sum squared deviations
a. Variance
3. Average squared deviations
iv. Find standard deviation
1.  
2.   
f. SS: sum of squared deviations
i. So…variance=SS/n
ii. 2 ways to compute
1. definitional formula
Unlock document

This preview shows half of the first page of the document.
Unlock all 2 pages and 3 million more documents.

Already have an account? Log in

Get OneClass Notes+

Unlimited access to class notes and textbook notes.

YearlyBest Value
75% OFF
$8 USD/m
$30 USD/m
You will be charged $96 USD upfront and auto renewed at the end of each cycle. You may cancel anytime under Payment Settings. For more information, see our Terms and Privacy.
Payments are encrypted using 256-bit SSL. Powered by Stripe.