Stat 221 Exam 2

Front 1

Values of one variable tend to occur with certain values of another variable; detected when the conditional distribution differ from the marginal distribution and from each other.

Back 1

association

Front 2

A condition where th mean of the statistic values differs from the parameter that the statistic estimates

Back 2

bias

Front 3

The name of the statement telling us that the sampling distribution of x-bar is approximately normal whenever the sample is large and random.

Back 3

Central Limit Theorem

Front 4

The distribution of the values in a single row (or column) of a two-way table.

Back 4

conditional distribution

Front 5

a statistical tool for monitoring the input or output of a process

Back 5

control chart

Front 6

+/- 3 (sigma/root(N))

Back 6

control limits

Front 7

a measure of the strength of the linear relationship between two quantitative variables

Back 7

correlationcoefficient

Front 8

events that cannot occur simultaneously

Back 8

disjoint events

Front 9

A list of the possible values of a variable together with the frequency. (probabilities can be substituted for frequency)

Back 9

distribution of variable

Front 10

A single outcome or a combination of outcomes from a random phenomenon.

Back 10

event

Front 11

Predicting a Y value using a value of X that is outside of the range of X values used to obtain the regression equation when it is included in the computations. This prediction could be very far off.

Back 11

extrapolation

Front 12

Results from statistical analyses performed on non- random samples.

Back 12

garbage

Front 13

Using results from a sample statistics value to draw conclusions about the population parameter.

Back 13

inference

Front 14

An observation that substantially alters the value of slope and y-intercept in the regression equation when it is included in the computations

Back 14

influential observation

Front 15

The fact that the average of observed values in a sample will get closer and closer to mu as the sample size increases.

Back 15

law of large numbers

Front 16

The basis for hypothesis testing and confidence interval estimation

Back 16

laws of probability

Front 17

A method for finding the equation of a line that minimizes the sum of squared residuals

Back 17

least squares

Front 18

The line with the smallest sum of squared residuals

Back 18

least squares regression line

Front 19

a variable that is not measured but explains association between two variables that are measured.

Back 19

lurking variable

Front 20

The distribution of the values in the "total" row (or the "total" column) of a two-way table.

Back 20

marginal distribution

Front 21

the mean of all the sample means from all possible samples of size n from a population; equals mu

Back 21

mean of the sampling distribution of x bar

Front 22

the mean of the population

Back 22

mu

Front 23

a condition where values of one variable occur independent of values of another variable; detected when the conditionals of a two-way table equal the marginal distribution(and each other)

Back 23

no association

Front 24

the difference between the observed statistic and the claimed parameter value

Back 24

observed effect

Front 25

one sample mean outside the 3 standard deviation of population, proportion of a population, respectively

Back 25

out-of-control process

Front 26

An observation that falls outside the overall pattern of the data set.

Back 26

outlier

Front 27

A characteristic of a population that is usually unknown; this could be mean, median, proportion, standard deviation computed on all the data from the population.; a parameter does not have variability

Back 27

parameter

Front 28

parameter symbols

Back 28

mu, sigma, p (mean of pop, standard dev. of pop, proportion of a pop., respectively)

Front 29

High values of one variable tend to associate with high values of another variable.

Back 29

positive association

Front 30

A measure of the proportion of times an outcome occurs in a very long series of repetitions that gives us an indication of the likelihood of the outcome.

Back 30

probability of an outcome

Front 31

Sequence of operations used in production, manufacturing, etc

Back 31

process

Front 32

A process whose inputs and outputs exhibits natural variation when observed over time

Back 32

process in statistical control

Front 33

A chart plotting the means x-bar of regular samples of size n against time; this chart is used to asses whether the process is in control

Back 33

quality control chart

Front 34

The type of data required for regression analysis

Back 34

quantitative bivariate

Front 35

the symbol for correlation coefficient

Back 35

r

Front 36

the percentage of total variation in the response variable, Y, that is explained by the regression equation; in other words, the percentage of total variation in the response variable, Y, that is explained by the explanatory variable, X

Back 36

r^2

Front 37

A phenomenon that describes the uncertainty of individual outcomes but gives a regular distribution of the outcomes in the long run

Back 37

random

Front 38

A formula for a line that models a linear relationship between two quantitative variables.

Back 38

regression equation

Front 39

The observed y minus the predicted y; denoted: y-(yhat)

Back 39

residual

Front 40

a diagnostic plot of the explanatory variable versus the residuals used to asseshow well the regression line fits the data; complete scatter in a shoe box pattern is good whereas a megaphone pattern denotes unequal variance in Y=s across all levels of X and curvature in the form of a smile or a frown denotes that the linear model is not best for that data.

Back 40

residual plot

Front 41

The random variable of the sampling distribution of x bar

Back 41

sample mean

Front 42

The list of all possible outcomes of a random phenomenon

Back 42

sample space

Front 43

A distribution of a stat.; a list of all the possible values of a statistic together with the frequency (or probability) of each value.

Back 43

sampling distribution

Front 44

A list of all possible values for x-bar together with the frequency (or probability) of each value; in other words, the distribution of all x-bar's from all possible samples.

Back 44

sampling distribution of x-bar

Front 45

The variability of sample results from one sample tothe next; something we must measure in order to effectively do inference.

Back 45

sampling variability

Front 46

A two dimensional plot used to examine strength of relationship between two variables as well as direction and type of relationship.

Back 46

scatterplot

Front 47

a condition where the percentages reverse when a third (lurking) variable is ignored; in other words, a condition leading to misinterpretation of the direction of association between two variables caused by ignoring a third variable that is associated with both of the reported variables.

Back 47

Simpson's paradox

Front 48

Using random numbers to imitate chance behavior

Back 48

simulation

Front 49

A measure of the average change in the response variable for every one unit increase in the explanatory or independent variable.

Back 49

slope

Front 50

A measure of the variability of the data

Back 50

standard deviation

Front 51

standard deviation of x-bar

Back 51

a measure of the variability of the values of the statistic x-bar about mu; a measure of the variability of the sampling distribution of x-bar; in other words, the average amount that the statistic, x-bar, deviates from its associated parameter. Computed(sigma/root(n))

Front 52

A number computed from sample data (without any knowledge of the value of a parameter) used to estimate the value of the parameter.

Back 52

statistic

Front 53

x-bar, s, p-hat

Back 53

statistic symbols

Front 54

A procedure used to check a process a regular intervals to detect problems and correct them before they become serious

Back 54

statistical process control

Front 55

Results of a study that differ too much from what we expected because of randomization to attribute to chance variation; the difference between the obseerved statistic and the claimed parameter value is too large to be due to chance. Results are classified as statistically significant when P-value>alpha

Back 55

statistically significant

Front 56

the residuals are squared and added; denoted SSE

Back 56

sum of squared residuals (or error)

Front 57

Procedure used to asses the evidence against a claim (hypothesis) about the value of a parameter

Back 57

test of significance

Front 58

A number that summarizes the data for a test of significance, usually used to obtain P-value.

Back 58

test statisitic

Front 59

The sum of the squared deviations of the Y observations about their mean, Y-bar.

Back 59

total variation in Y

Front 60

A table containing counts for two categorical variables. It has r rows and c columns.

Back 60

two-way table

Front 61

unbiased

Back 61

a condition where the mean of the statistic values equals the parameter that the statistic estimates.

Front 62

The sum of squared residuals

Back 62

unexplained variation

Front 63

the symbol for the explanatory variable

Back 63

X

Front 64

A plot of sample means over time used to asses whether a process is in control

Back 64

x-bar chart

Front 65

The symbol for response variable

Back 65

Y

Front 66

the symbol for predicted y

Back 66

y-hat

Front 67

The z-value obtained from table C corresponding to a desired level of confidence; used in computing a confidence interval

Back 67

z

Front 68

z-score

Back 68

a measure of the number of standard deviations of a value or observation from the mean