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Lecture 3 2-3-17

Quantifying Data and Statistical Analysis

I. Quantifying Data

a. Using a number to summarize variables

i. Variables – any measurable characteristic that varies

b. This allows us to perform statistical analysis

II. Two methods of examining quantified data

a. Mean – an arithmetic average of scores in a

distribution

b. Standard deviation – the amount of

variability about the mean

i. A computed measure of how much

scores vary around the mean

III. Correlation

a. The degree of variability shared by two

variables

i. Association between two variables

b. Positive correlation

i. Example – height and weight

ii. As one increases, the other also increases

c. Negative correlation

i. Example – leisure time and work time

ii. As one increases, the other decreases

d. No correlation

i. Example – SAT score

ii. A change in one variable has no effect on the other variable

e. Correlation coefficient

i. Denoted with the letter r

ii. Ranges from -1 < r < 1

1. -1 represents a perfect negative correlation, white positive 1 represents

a perfect positive correlation

IV. Comparing non-numeric variables

a. Categorical variables are non-numeric

https://fisherdong.wordpress.com/2011/03/25/positive-and-negative-correlation/

http://www.slideshare.net/nilanjanbhaumik9/measures-of-dispersion-43610696

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