AP Statistics Vocabulary

data on which both sides are fairly the same shape and size. "Bell Curve"
value of a population (typically unknown)
a calculated value about a population from a sample(s).
the middle point of the data (50th percentile) when the data is in numerical order.
allows statisticians to distinguish between usual and unusual occurrences.
Standard Deviation
measures the typical or average deviation of observations from the mean
Skewed Right
mean is a larger value than the median.
is a standardized score. This tells you how many standard deviations from the mean an observation is.
Normal Model
is a bell shaped and symmetrical curve.
As σ increases the curve flattens.
As σ decreases the curve thins.
Mutually Exclusive
A and B have no intersection. They cannot happen at the same time.
if knowing one event does not change the outcome of another.
Law of Large Numbers
as an experiment is repeated the experimental probability gets closer and closer to the true (theoretical) probability.
Correlation Coefficient (r)
is a quantitative assessment of the strength and direction of a linear relationship. between -1 and 1.
Least Squares Regression Line (LSRL)
is a line of mathematical best fit. Minimizes the deviations
(residuals) from the line. Used with bivariate data.
Residual (error)
is vertical difference of a point from the LSRL. They should all add to zero. Is the difference between the observed and expected value.
Coefficient of Determination (r-squared)
gives the proportion of variation in y (response) that is explained by the relationship of (x, y).
LRSL cannot be used to find values outside of the range of the original data.
Influential Points
are points that if removed significantly change the LSRL.
a complete count of the population. Disadvantages of this: Not accurate, Expensive, Impossible to do
Simple Random Sample
one chooses so that each unit has an equal chance and every set of units has an equal chance of being selected.
Stratified Sampling
divide the population into homogeneous groups then SRS from every group. [Observational studies]
Cluster Sampling
Usually can be based on location. Select a random location and sample ALL at that location. Divide the population into heterogeneous groups and SRS a certain amount of groups. Take all members/things in that group.
favors a certain outcome, has to do with center of sampling distributions - if centered over true parameter then considered unbiased
Voluntary Response Bias
people choose themselves to participate.
Convenience Sampling
ask people who are easy, friendly, or comfortable asking.
some group(s) are left out of the selection process.
Nonresponse Bias
someone cannot or does not want to be contacted or participate.
Control Group
a group used to compare the factor to for effectiveness - does NOT have to be placebo
Single Blind
a method used so that the subjects are unaware of the treatment (who gets a placebo or the real treatment).
Double Blind
neither the subjects nor the evaluators know which treatment is being given.
A MUST for EVERY experimental design. Uses many subjects to quantify the natural variation in the response.
Completely Randomized Design
all units are allocated to all of the treatments randomly [Experiment]
Randomized Block
units are separated based on a KNOWN factor. Then randomly assign treatments in each group -reduces variation
Matched-Pair Design
Once a pair receives a certain treatment, then the other pair automatically receives the second treatment.
OR individuals do both treatments in random order (before/after or pretest/post-test)
Assignment is dependent
Confounding Variables
are where the effect of the variable on the response cannot be separated from the effects of the factor being tested - happens in observational studies - when you use random assignment to treatments you do NOT have this!
reduces bias by spreading extraneous variables to all groups in the experiment. MUST have in EVERY experiment
Binomial Probability
Trials have two outcomes; Trials are independent; and most importantly, the number of trials are fixed!
Geometric Probability
two mutually exclusive outcomes, each trial is independent, probability (p) of success is the same for all trials. (NOT a fixed number of trials)
Sampling Distribution
is the distribution of all possible values of all possible samples. Use normalcdf to calculate probabilities
Central Limit Theorem
when n is sufficiently large (n > 30) the sampLING distribution is approximately normal even if the population distribution is not normal.
Lurking Variable
is a variable that is not included as an explanatory or response variable in the analysis but can affect the interpretation of relationships between variables. It can falsely identify a strong relationship between variables or it can hide the true relationship.
is a way to model random events, such that simulated outcomes closely match real-world outcomes
Placebo effect
A remarkable phenomenon in which a fake treatment, can sometimes improve a patient's condition simply because the person has the expectation that it will be helpful
A graphical display that represents a frequency distribution by means of rectangles whose widths represent class intervals or "bins"
Interquartile Range
A numerical description of a distribution requires both a measure of center and a measure of spread
"X bar"
Sample mean
68-95-99.7 rule
percentage of data within 1, 2, and 3 standard deviations of a normally distributed dataset.
Explanatory variable
Helps explain or influence change in a response variable
Response variable
Measures an outcome of a study
A specific condition applied to the individuals in an experiment.
"p hat"
Sample proportion used to estimate unknown parameter
unbiased estimator
A statistic used to estimate a parameter, if the mean of its sampling distribution is equal to the value of the parameter being estimated.