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PSYC 1010
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David Stanley
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Midterm

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Psychology

PSYC 1010

David Stanley

Winter

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Psych 1010 midterm 1 study notes
Chapter 1
- Branches of statistics
o Descriptive
Organize summarize and communicate numerical information
o Inferential statistics
Using data collected from a sample to draw conclusions about
a population
- Population: set of all observations in a particular study
- Sample: A set of observations drawn from a population of interest for
inclusion in a study
- Parameter: value that described population
- Statistic: value that describes sample
- Variables
o Discrete variables
Can only take on specific values (integers)
Measures how many
o Continuous variables
Full range of values
Measures how much
o Always discrete:
Nominal variables
Observations with names or categories as values
Qualitative not quantitative differences between
categories
Ordinal variables
Ranked by size or magnitude
Know rank but no info about size intervals
o Scale variables
Sometimes discrete, sometimes continuous
Interval
Observations of ordered numerical values with
intervals of equal size, no meaningful zero
Ratio
Observations of ordered numerical values with
intervals of equal size, but there is a meaningful zero
Can form ratios
- Operational definition
o Set of procedures used to measure or manipulate a variable
- Confounding variable
o Uncontrolled variable that it unintentionally allowed to vary
systematically with the independent variable
- Reliability o Consistency of measure
- Validity
o Extent that the test measures what it is supposed to measure
- Research designs
o Correlational method
Association between two or more variables
No manipulation, only observation
o Experimental method
Randomly assign participants to levels (groups) of the
independent variable
Able to make causal conclusions (effect of IV on DV)
- Control confounding variables
o Random assignment to groups
Chapter 2
- Frequency distributions: gives number of times each possible value of a
variable occurs in a data set
o Frequency table
o Grouped frequency table
Used for large range of scores and data to several decimal
places
Full range = Xmax – Xmin +1
Use 10 intervals
No gaps
o Frequency histograms
Represent scale data (interval and ratio)
Can have polygon overlay (lines over bars)
o Frequency polygon
Also represent scale data (looks more like line graph)
o Grouped histogram
Use middle of interval at bottom (e.g 7.5 not 0-14.99)
o Grouped polygon
Same as histogram, use middle point
- Histograms vs. bar graphs
o Histograms are used for interval or ratio scales of measurement, bars
touch
o Bar graph bars do not touch, used for nominal or ordinal data
- Normal distribution
o Bell-shaped
o Symmetrical around the mean
o Unimodal (only one peak)
- Skewed distributions
o Positive skew
tail more to the right
May reflect floor effect (you can’t score any lower) o Negative skew
More to the left
May reflect ceiling effect (you can’t score any higher)
Chapter 3
- Misleading with Data
o False face validity lie
Method seems to represent what it says, but doesn’t actually
(e.g. using yelling as a measure of aggression)
o Biased scale lie
Scaling to skew results (e.g. 3 positive words out of 5 options)
o Sneaky sample lie
Participants are preselected to provide desired data
o Extrapolation lie
Assumes knowledge outside of study (predict things that can
not be proven)
o Inaccurate values lie
Using scaling to distort portions of the data (e.g. graph about
doctors)
o Outright lie
Making up data
- Graphs
o Scatterplot
Show relationship between two scale variables (IV on x and DV
on y)
Determine if linear or non-linear relations
o Line graphs
Line of bet fit on

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