Ap Statistics Ch2-4 Terms

Front 1

inflection points

Back 1

the points at which the curve changes from falling more steeply to falling less steeply. They are located at a distance equal to the standard deviation on either side of the mean

Front 2

standardizing

Back 2

changing to units of size σ about μ as a center

Front 3

Z-score

Back 3

standardized value that tells hows many standard deviations the original observation falls away from the mean and in which direction z= (x-μ)/σ

Front 4

standard normal distribution

Back 4

N(0,1)- a normal distribution with a mean of 0 and a standard deviation of 1

Front 5

Z table

Back 5

the value in the table shows the proportion of observations to the left of the z score

Front 6

normal probability plot

Back 6

used to assess normality. if the data is approximately normal, the normal probability plot will be roughly linear.

Front 7

response variable

Back 7

dependent variable -y- measures the outcome of a study

Front 8

explanatory variable

Back 8

independent variable -x- attempts to explain the observed outcomes

Front 9

scatterplot

Back 9

shows the relationship between two quantitative variables

Front 10

correlation (r)

Back 10

measures the direction and strength of a linear relationship

Front 11

least-squares regression

Back 11

a method for finding a line that summarizes the relationship between two quantitative variables

Front 12

coefficient of determination (r^2)

Back 12

the fraction of variation in the values of y that is explained by the least-squares regression of y on x

Front 13

residual

Back 13

the difference between an observed value of the response variable and the value predicted by the regression line

Front 14

residual plot

Back 14

a scatterplot of the regression residuals against the explanatory variable

Front 15

outlier

Back 15

an observation that lies outside the overall pattern of teh other observations

Front 16

influential observation

Back 16

an observation whose removal markedly changes the result of the calculation. Points that are outliers in the x direction of a scatterplot are often influential for the LSRL

Front 17

transforming the data

Back 17

applying a function (i.e. log or square root) to a quantitative transforming variable

Front 18

extrapolation

Back 18

the use of a regression line for prediction far outside the domain of values of the explanatory variable

Front 19

lurking variables

Back 19

a variable that is not among the explanatory or response variables in a study and yet may influence the interpretation of relationships among those variables

Front 20

confounding

Back 20

two variables, either explanatory or lurking, are confounded when their effects on a response variable cannot be distinguished from each other

Front 21

two way table

Back 21

describes two categorical variables

Front 22

marginal distributions

Back 22

totals at the right and bottom of a two way table

Front 23

simpson's paradox

Back 23

reversal of the direction of a comparision or an association when data from several groups are combined to form a single group