Level 231
Level 233

#### 89 words 0 ignored

Ready to learn
Ready to review

## Ignore words

Check the boxes below to ignore/unignore words, then click save at the bottom. Ignored words will never appear in any learning session.

**Ignore?**

What is a type 1 error?

when H₀ is true and you reject H₀

What is a type 2 error?

when H₀ is false and you accept H₀

the significance level,

What is the value of α called? what values do we usually take as α?

t = r(√(n-z)/(1-r²))

To use standard tables you should compute the t value, how do you do this?

the critical value c which satisfies;

What do you find when looking in the t tables?

When would you reject H₀?

if the value of |t|>c at level α.

normally distributed data.

What kind of distribution uses a t test?

H₁: p ≠ 0

If H₀: p = 0, then what is the alternative H₁?

a two-tailed test.

If you include H₀ and H₁ what type of test is this?

When do you use a one-tailed test?

when you have stated what the connection between the data is in your hypothesis.

When do you use a two-tailed test?

when you have stated there is a connection but not the direction in you hypothesis.

Population

the entire group of items or individuals for which a sample is taken (the entire American _______________________, New jersey is a sample)

parameter

Number that describes a population

GOAL

Estimation, confidence interval, hypothesis testing

Statistic

A number that describes a sample

Response variable

The variable being studied by the experimenter. The experiment will investigate how the response variable behaves when the investigator manipulates one or more explanatory variables or factors.

lurking variable

A variable other than x and y that simultaneously affects both variables, accounting for the correlation between the two.

Randomization

The best defense against bias; each individual is given a fair, random chance of selection.

Blocking

Using extraneous factors to create groups blocks that are similar. All experimental conditions are then tried in each block.

Control

Holding extraneous factors constant so that their effects are not confounded with those of the experimental conditions.

prospective study

An observational study in which subjects are followed to observe future outcomes.

retrospective study

An observational study in which subjects are selected and then their previous conditions or behaviors are determined.

Experimental study

assigns to each subject a treatment and then observes the outcome on the response variable

Treatments

experimental conditions which correspond to assigned values of the explanatory variable

observational study

The researcher observes the experimental units in their natural setting and records the variable(s) of interest. The researcher makes no attempt to control any aspect of the experimental units.

Simple random sample

each possible sample is equally likely

Clusters random sample

identify clusters of subjects, take simple random sample of the clusters

stratified random sample

A sampling design in which the population is divided into several subpopulations, or strata, and random samples are then drawn from each stratum.

census

Used to measure a variable for every unit of a population.

survey

a question or set of questions designed to collect data

Observational

subjects responses are recorded under various conditions that are not manipulated by the researcher

Designed

subjects responses are recorded under various experimental conditions that are manipulated by the researcher

sampling frame

The list of possible subjects who could be selected in a sample.

experimental units

Individuals on whom an experiment is performed.

Randomized block

a block design with random assignment of treatments to units within blocks

Variable

an alphabetic character representing a number, called the value, which is either arbitrary or not fully specified or unknown. It is usually a letter like x or y.

Categorical

What type of data is the color of M&M's?

Quantitative

observations on it take numerical values that represent different magnitudes of the variable

Discrete

is a quantitative variable that is usually a count such as 0, 1, 2, 3

Continuous

is a quantitative variable that has a continuum of infinitely many possible values

frequency table

a data display that shows how often an item appears in a category

Pie Chart

Graphical representation of data in the form of a circle containing wedges.

Bar graph

Bars do not touch; categorical data is typically on the horizontal axis; to describe: comment on which occurred the most often or least often

dot plot

graph with each individual entry

Stem-and-leaf plot

it displays individual observations

Histogram

A bar graph depicting a frequency distribution. The height of the bars indicates the frequency of a group of scores.

distribution

The _____________________________ of a var. gives: possible values of the variance; the relative frequency of each value.

skew

they have no relationship

Skewed to the left

the left tail is longer than the right tail

Skewed to the right

the right tail is longer than the left tail

Mean

the sum of all the values divided by the number of values

Median

A segment or Ray that joins a vertex to the midpoint of the opposite side

Range

The difference between the greatest number and the least number in a set of data.

Confounding variables

when we are uncertain which two variables is causing an effect

Blind

subjects don't know the treatment to which they are assigned

Double blind

whoever has with subjects and subjects are not aware of the treatment

outliers

Values that are very unusual in the sense that they are very far away from most of the data.

Z score

Standardized score

Mean and Median

describe the center of a distribution

Range and Standard Deviation

describe the variability of the distribution

Standard Deviation

Square Root of the Var.

Association

exists between two variables if a particular value for one variable is more likely to occur with certain values of the other variable

Contigency table

is a display for two categorical variables

Scatter plot

is a graph used to determine whether there is a relationship between paired data. Scatter plots can show trends in data.

Positive association

as x goes up, y tends to go up

Negative association

as x goes up, y tends to go down

correlation

summarizes the direction of the association between two quantitative variables and the strength of its linear trend

regression line

predicts the value for the response variable y as a straight line function of the value x of the explanatory variable

Residuals

The vertical deviation between the observations and the LSRL

Least Squares Method

method produces the line that has the smallest value for the residual sum of squares

R squared

it is the percentage of the response variable variation that is explained by a linear model

context

Tells who was measured, what was measured, how the data were collected, where the data was collected, and when and why the study was performed.

data

A collection of information gathered for a purpose. Data may be in the form of either words or numbers.

Data Table

An arrangement of data in which each row represents a case and each column represents a variable.

case

Individual about whom or which we have data.

categorical variable

A variable that names categories (words/numbers)

Quantitative Variable

A variable in which the numbers act as numerical values - always have units.

units

A quantity or amount adopted as a standard of measurement, such as dollars, hours, or grams.

area principle

In a statistical display, each data value should be represented by the same amount of area.

bar chart

Shows a bar whose area represents the count (or percentage) of observations for each category of a categorical variance.

Marginal Distribution

In a contingency table, the distribution of either var. alone.

Conditional Distribution

The distribution of a var. restricting the who to consider only a smaller group of individuals.

Independence

Variables are ________________ if the conditional distribution of one variables is the same for each category of the other.

simpson's paradox

When averages are taken across different groups, they can appear to contradict the overall averages.

stem-and-leaf display

shows quantitative data values in a way that sketches the distribution of the data

dotplot

Consists of a graph in which each data value is plotted as a point (or dot) along a scale of values. Dots representing equal values are stacked.

Shape

To describe the _________ of a distribution, look for: single vs. mult. modes; symmetry vs skewness; outliers and gaps.

Center

Each regular polygon has a center because it can be inscribed in a circle.

spread

A numerical summary of how tightly the values are clustered around the center. Measures: IQR, Standard Dev.