# PSYCH 100A Lecture Notes - Lecture 3: Central Tendency, Standard Deviation

69 views2 pages Distributions
Can be a graph/table/mathematical function describing the frequency of each score
Frequency describes how often something occurs
The normal distribution is a theoretical function that describes many physical and
psychological traits
o Apex of the curve is the highest occurrence at the middle
Center of distribution is important
Typical score
o Lower tail/upper tail is where the curve levels off
Region where uncommon scores occur
o Bell-curve
Theoretical vs. Empirical Distributions
Center: represents typical response, lower spread (high peak)
Spread - (or variability) like standard deviation, sample of scores where people are more
similar to one another. Low peak
o High variability - low peak
o Low variability - high peak, scrunched up
Shape - depends on where the peak is
o In what area do most scores fall?
Positively skewed distribution
o Most scores in the low range, high scores are less frequent
o Tail point towards the positive side of the number line
Negatively skewed distribution
o Most scores in the high range, low scores are less frequent
o Tail points toward the negative side of the number line
Uniform distribution
o All scores equally likely
Distributions
How can we summarize the distribution
Bar Graphs and Histograms
Bar graphs: categorical variable
o Put spaces between the bars to categorize it, not continuous number line but bins
o Order of the bars are arbitrary. Can't say that it is positively/negatively skewed.
Histograms: continuous variable
o No spaces between the bars
o Kernel Density Plot - connects the heights of all the bars in a histogram
Represents a continuous function
Frequency Distributions
A tabular display of the information from the bar graph
Cumulative Percent
The percentage at or below a score
Accumulate the two percentages from the bottom two categories
o "15% of the people participating in the study were at or below inappropriate"
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