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QMP Vocab Week #1

TermDefinition
Hypothesis statement of the relationship among variables, not a question
Operational definition exactly how to measure the variable
Collect Data results of an experiment in numbers, needs to be usable
Analyze results getting the numbers through formulas
Interpret results the meaning, relating back to hypothesis
Share results publish or make public knowledge your findings
Statistics a set of tools concerned with the collection, organization, and analysis of data, has two branches: descriptive and inferential
Data the numbers
Descriptive describes data, ex. class average
Inferential to make inferences of the data, ex. our class average is all class averages on campus
Variable anything that can take on different values or amounts, two types: independent and dependent
Independent the researcher manipulates, control or experimental group, used to group people
Dependent measurement of behavior, effect not cause
Correlation relationship between two variables
population complete collection of anything, regardless of size of collection
sample subset of population, measured to talk about populations, goal to be unbiased
mean mew
number of anything N
parameters numerical summary characteristics of population, can measure about a populations
statistics numerical summary characteristics of a sample
mean of sample - over x
scaling the assigning of numbers to objects or events
4 scales of measurements nominal scale, ordinal scale, interval scale, ratio scale
nominal scale assigns a name or label to objects or events, can be #'s, ex. barcodes
ordinal scale objects or events in rank order, just rank alone, not equality, ex. favorite bands
interval scale equal intervals between number, ranks are equal, ex. degrees f to c
ratio scale zero means absence of measurements, true zero, ex. height
Frequency Distribution creating a table of the data that shows the number of times a given group of scores occurs, construction varies, all have x and f columns,
x variable
f frequency
cf cumulative frequency
cumulative frequency number of times a value occurs up to and including that frequency
rf relative frequency
relative frequency the proportion of people on each row, always adds to one
percentage rf x 100
crf cumulative relative frequency
cumulative relative frequency rf up to and including all values, add to one
c% crf x 100, % of people up to and including any score level
results of frequency distribution lost almost all richness, organized
graphing must label axis, y axis should be 3/4 that of x axis, y axis should use full range, always start y axis at zero
histogram bars touch, good with graphed frequency distribution
line graph connect the points
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