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PSYCH 210: Exam #1
A characteristic or condition that varies and has different values in different people or at different times |
Variable |
Measuring variables |
data |
Scales of Measurement |
NOIR |
to classify
-Diagnosis, Genotype, Dead/Alive etc. |
Nominal (Qualitative) |
Order-unequal intervals
-social rank, race finish, birth order, intervals can be different |
Ordinal (Qualitative) |
Distance, magnitude
-equal intervals, arbitrary "0", temperature (C,F), opinion |
Interval (Quantitative) |
Origin
-Natural "0", temperature in K, brain volume, # of convictions, time |
Ratio (Quantitative) |
Describes data |
Descriptive statistics |
Lets us infer using samples to study populations, uses probability |
Inferential statistics |
Help us understand populations
-represents population in a study
-has "n" individuals |
Sample |
The entire set/group of individuals you could potentially observe |
Population |
characteristics of populations |
Parameters |
characteristics of samples |
Statistics |
(Hopefully small) discrepancies that almost always occur
-Larger sample should have smaller sampling error from populations values |
Sampling error |
Links samples and populations
-replication is important |
Probability |
What measurement scale? Inches |
Ratio |
What measurement scale? Weather conditions |
Nominal |
What measurement scale? Rank order of favorite NCAA teams |
Ordinal |
What measurement scale? Weight in pounds |
Ratio |
What measurement scale? Religious affiliation |
Nominal |
What measurement scale? Distance |
Interval |
An equal chance for inclusion in sample
-each set of members is equally likely
-discrepancy of M from Mu is random |
Random Selection |
Sample where demographics are in proportion (Good) |
Stratified random sample |
Sample of only Intro Psych students (randomly selected)
(Not as good) |
Convenience sample |
Least useful sample, be cautious (Bad)
-biased |
Self-selected sample |
-Pre-existing patterns
-preexisting groups compared (difference in mean?)
-don't know if causal or not |
Correlation |
-Artificially create groups that differ on a variable
-record differences in another variable
-what's the advantage? Causation |
Experiment |
Measure naturally occurring associations
-quantify pattern in 2 observed random variables (x,y)
-compares means |
Nonexperimental, Correlational Studies |
Finding cause
1) Manipulation of Independent variable
2) Control of confounding variables
3) Observe dependent variable |
Experimental Study |
A factor manipulated by the experimenter. The focus of the study. |
Independent variable |
Factor that may change in response to an independent variable. Can be multiple |
Dependent variable |
3 Preventing confounds practices |
1) Random assignment - to treatment/control condition
2) Holding constant - same treatment for everyone (e.g. all surgeons right handed)
3) Matching (participants) e.g. anxiety level, R/L handed |
Internal attributes or characteristics that can't be directly observed but are useful for explaining/describing behavior |
Constructs |
Identifies an observable variable theoretically related to a construct
-defines the construct in terms of those measurements |
Operational Definitions |
Typically whole, countable numbers with no intermediate values possible |
Discrete variables |
Free to choose precision, indefinitely divisible categories
-real limits=-1/2 unit, +1/2 unit |
Continuous variables |
Shows the number of individuals (f) in each category (x) on a scale of measurement
-organizes and reveals trends |
Frequency Distribution |
"Intervals" of X values
-summarize, condense measurement categories
-lose precise frequencies
-O/I/R scales |
Grouped Frequency Distributions |
Unequal intervals that don't touch
-Nominal, Ordinal |
Bar Graph |
Quantitative scale, extends to real limits
-Ratio, Interval |
Histogram |
Has to start and end at bottom (0)
-Ratio, Interval
-rarely used, except published research |
Polygon |
Positive skew: Too hard
Negative skew: Too easy |
Floor Effect |
Higher percentiles always equal higher _______ |
scores |
The sum of the scores divided by the number of scores |
Mean |
Distance from the Mean |
Deviation score |
The sum of the Deviation scores = |
0 |
M=20
-add 1 to every score what is the new mean? |
21 |
(SumX1 + SumX2) / (n1 + n2) |
Weighted Mean |
Mean is not appropriate for _____ & _______ scales |
Nominal, Ordinal |
Cares more about rank order than number values
-midpoint in ordered list of scores
-value dividing distribution in half |
Median |
Most frequent category or score
-always the peak in distribution
-always actual, observed value
-can have multiple
-N,O,I,R
-highest frequency |
Mode |
Positive skew: left to right (M,Mdn,Mo)? |
Mean, Median, Mode |
Negative skew: left to right (M,Mdn,Mo)? |
Mode, Median, Mean |
For a negatively skewed distribution with a Mode of X=25 and a mean of M=20, the Median is probably? |
Between 20 and 25 |
Describes a central point of the distribution |
Central Tendency |
How scattered/spread out the scores are
-used to describe/summarize
-used as a basis for most inferential stats |
Variability |
Low variability = |
Better representation of sample |
High variability = |
Unrepresentative sample common
-harder to detect relationships |
Max distance between scores
Continuous: Xmax - Xmin
Discrete: Xmax - Xmin +1 |
Range |
Distance covered by middle 50% of the distribution
-useful with vary skewed distribution |
Interquartile Range |
The average distance between a score and the mean |
Standard Deviation |
Average squared distance from the mean |
Variance |
The square root of variance |
Standard deviation |
Sum of Squares (SS) |
SS=Sum(X-M)^2 |
Convey each score's distance from the mean in standard deviation units
-rarely used in applied settings (decimals, negative numbers are confusing) |
Z-Score |
Body-percentile rank
Tail-proportion higher than the score |
Positive Z-Score |
Body-proportion higher than the score
Tail-percentile rank |
Negative Z-Score |
p + q= |
1 |