Basic Statistics for Research Exam 1

population

the entire group the researcher wants to understand; its size is N

sample

the smaller group actually observed; its size is n

parameter

a numerical characteristic of a population, such as μ, σ, or p

statistic

a numerical characteristic calculated from a sample, such as x̄, s, or p

variable

a characteristic recorded for each individual or object

simple random sampling method

every possible sample of size n has an equal chance of selection

use a random-number method

systematic sampling method

choose a random starting point, then select every kth individual

every kth person or item

stratified sampling method

divide into natural groups, randomly choose whole groups, and survey all or many members in them

some from each group

cluster sampling method

divide into natural groups, randomly choose whole groups, and survey all or many members in them

choose entire groups

convenience sampling method

use individuals who are easiest to reach

fast, but often biased

qualitative variables

categories or labels; arithmetic is not meaningful

ex: payment type, blood type

quantitative discrete variables

countable numerical values, usually whole numbers

ex: number of visits

quantitative continuous variables

measurements that can take any value in an interval

ex: distance, time, weight

relative frequency

class frequency ÷ total number of observations

cumulative frequency

the running total of frequencies through a class

class width

difference between consecutive lower class limits (or consecutive class boundaries)

class midpoint or class mark

(lower class limit ÷ upper class limit) ÷ 2

bar graph or Pareto chart

compare qualitative categories; Pareto bars are ordered from greatest to least greatest frequency

pie chart

show categories as parts of a whole

histogram, frequency polygon, dot plot ,stem and leaf

display the distribution of quantitative data

box plot

display the five-number summary and possible outliers

scatterplot

display the relationship between two quantitative variables

skewed right distribution

long tail extends towards larger values

mean usually > median

skewed left distribution

long tail extends toward smaller values

mean usually < median

outcome

one possible result of a chance process

event

a set of one or more outcomes; a simple event has one outcome and a compound event has more than one

theoretical probability

based on equally likely outcomes and a mathematical model

empirical probability

observed frequency ÷ total number of trials

subjective probability

an informed judgment based on experience or available information