Transcript 1-Powerpoint_-_Statistics

Psychology and Statistics
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Interpreting Data
(Ch. 1 Myers and Ch. 2 Barron’s)
Descriptive Statistics
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Descriptive statistics – describes a set of
data
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Measures of Central Tendency
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Measures of Variation
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Goal is to determine the center of the distribution
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Goal is to describe the diversity of the distribution
Measures of Central Tendency
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• MEAN - Average
• MEDIAN – Middle, 50th %
• MODE – Most frequently occurring score
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Mean
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• Most frequently used measure of central
tendency but can be distorted by outliers
(extremes). If the distribution includes
outliers, then the median is a better measure
of central tendency.
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– Ex. 2, 7, 8, 9, 10, 18
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Mean
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• If the distribution is not skewed it is called symmetrical.
Outliers skew the distribution. If there are high positive
outliers then the distribution is positively skewed. (more
low scores than high scores) If there are very low outliers
then the distribution is negatively skewed. (more high
scores than low scores)
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Symmetrical
Positively Skewed
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Negatively Skewed
Examples of Skewed
Distributions
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• 39,000 penniless people
• Geography Majors from UNC Chapel Hill
class of 84??
• Test average 65
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Measures of Variation
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• Range – the gap between the lowest and
the highest score
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Distribution of Value
Standard Deviation
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• THE BELL CURVE (IQ)
+ or – 1 Standard Deviation = 15 pts.
Remember Standard Deviation measures the
distance from the mean.
Mean of IQ = 100
What score is +1 SD? What score is – 1 SD?
+ and – 1 SD of IQ scores includes 68%
What score is + 2 SD? What score is – 2 SD?
+ and – 2 SD of IQ scores includes 95%
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Z Scores and Standard Deviation
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• Z scores measure the distance of a score
from the mean in units of standard
deviation. If the score is below the mean its
z score is negative. If it Is above the mean
then the z score is positive.
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– Consider this example. Mean of 100. Joe scores
90 and has a z score of -1. Sarah scores a 105.
What is her z score?
Inferential Statistics
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• Inferential Statistics determines if the findings
can be applied to a larger population from which
the sample was selected.
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– It is a goal of the researchers for the sample to be representative
of the population
– The extent to which the sample differs from the population is
known as sampling error.
– Statistical tests yield p values. The smaller the p-value the more
significant the results. The cutoff for findings being statistically
significant is p = .05. This means that there is a 5% chance that
the findings were by chance. P-value never equals 0 because we
can never be 100% certain that our findings were not due to
chance.
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Statistical Significance
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• When is the difference significant?
– Psychologists are conservative when it comes to declaring
some research statistically significant.
– Statistical significance – When the difference observed is
not likely to have occurred by chance.
– When samples averages are reliable and the difference
between them is large then the difference has statistical
significance
– When it is 5% or less likely to have occurred by chance,
then psychologist will say that there is statistical
significance.
– Be wary of statistical significance in homogeneous
samples – (these samples are homogeneous and not
practical to life application)
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Statistics can Lie
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• Examples of Statistics being used for selfish
purposes of politicians and/or corporations.
• Video:
• ECU study changing NC school start times
• Global Warming Studies funded by Exxon.
• NC HWY 74 By Pass studies and impact on
the environment.
• Health Care Debate - Lies, Lies and
Statistics
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