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Stats Unit 1 Test
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Gravity
Terms in this set (26)
discrete observation
can take on only specific values (e.g. whole numbers); no other values can exist between these numbers
continuous observation
can take on a full range of values (e.g., numbers out to several decimal places); an infinite number of potential values exists
nominal variable
variable with values that are categories or names
(have two or more categories, but which do not have an intrinsic order)
CATEGORICAL DATA
ALWAYS DISCRETE
nominal variable example
if we were looking at gender, we would most probably categorize somebody as either "male" or "female".
ordinal variable
a qualitative variable that incorporates an ordered position, or ranking
CATEGORICAL DATA
ALWAYS DISCRETE
Ordinal variable example
you might ask patients to express the amount of pain they are feeling on a scale of 1 to 10. A score of 7 means more pain that a score of 5, and that is more than a score of 3.
interval variable
a variable used for observations that have numbers as their values; the distance (or interval) between pairs of consecutive numbers is assumed to be equal.
(similar to an ordinal variable, except that the intervals between the values of the interval variable are equally spaced.)
QUANTITATIVE DATA
DISCREET OR CONTINUOUS
interval variable example
suppose you have a variable such as annual income that is measured in dollars, and we have three people who make $10,000, $15,000 and $20,000.
ratio variable
a variable that meets the criteria for an interval variable but also has a meaningful zero point
QUANTITATIVE DATA
ALMOST ALWAYS CONTINUOUS
ratio variable example
height, mass, distance and many more
scale variables
refers to interval and ratio variables
level
a discrete value or condition that a variable can take on
Reliability
consistency of measurement
Validity
the extent to which a test measures or predicts what it is supposed to
example of operational definition
intelligence may be operationally defined as what an intelligence test measures; if you wanted measure and define "life change" you could do this by giving people the Social Readjustment Rating Scale and then operationally define "life change" as the score on the social readjustment rating scale
between-groups research design
participants experience one and only one level of the independent variable
example of between-groups design
Lou has two groups of participants, one in the 50 degree room and one in the 85 degree room.
within-groups design
an experimental design in which each participant is presented with all levels of the independent variable
example of within-groups design
Emily gathers a bunch of volunteers and gives them a passage to read in a noisy room. Afterwards, she tests their memory of the reading passage. Then, she puts all of the volunteers into a room that's quiet and has them read another passage. Finally, she tests them on the passage they read in the quiet room.
frequency distribution vs. frequency table
frequency distribution describes the pattern of a set of numbers by displaying a count or proportion for EACH possible value of a variable. (level and score) A frequency table shows how many scores were at each value. Values are listed in one column while numbers of individuals with scores at that value re lined up in the second column. (level and frequency of scores for that value)
grouped frequency table
a visual depiction of data that reports frequencies within a given INTERVAL rather than the frequencies for a specific value
what is always on the y-axis of a histogram?
frequency
scatterplot
depicts the relationship between two scale variables. values for each variable labeled on either axis and a mark is made at the intersection of the two scores.
difference between proportion, probability, and percentage
proportion: # successes/# trials
probability: proportion we expect to see over time
percentage: proportion x 100
Type I error (alpha)
rejecting a correct null hypothesis
(false positive)
i.e. test is positive but woman is NOT pregnant
Type II error
failing to reject a false null hypothesis
(false negative)
i.e. test is negative but the woman IS pregnant
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