Sta 215 Chapter 2

Front 1

numbers and/or category labels that have been collected (measured) but have not yet been processed in any way

Back 1

raw data

Front 2

the entire group of objects or individuals under study, about which information is wanted

Back 2

population

Front 3

an individual object or person in the population

Back 3

unit

Front 4

The units are often called this if the population consists of people

Back 4

subjects

Front 5

a part of the population that is actually used to get information

Back 5

sample

Front 6

a characteristic of interest to be measured for each unit in the sample

Back 6

variable

Front 7

A collection of observations on one or more variables is called a?

Back 7

data set

Front 8

raw data that consists of group or category names

Back 8

qualitative variables

Front 9

If the category names do not necessarily have a logical ordering

Examples: eye color, country of residence.

Back 9

nominal variables

Front 10

If the category names do have a logical ordering

Examples: highest educational degree earned, shirt size (S, M, L, XL)

Back 10

ordinal variables

Front 11

raw data that consists of numerical values taken on each individual, have numerical values that are measurements (length, weight, and so on) or counts (of how many)

Back 11

quantitative variables

Front 12

variable is one for which you can count the number of possible values

Example: the number of correct answers on a multiple-choice test

Back 12

discrete

Front 13

variable can take on any value within a given interval.

Example: the amount of water poured into a 50-ml glass container.

Back 13

continuous

Front 14

In general, the value of the ___________ variable for an individual is thought to partially explain the value of the ________ variable for that individual.

Back 14

explanatory; response

Front 15

provides the possible values that a variable can take on and how often these possible values occur

Back 15

distribution

Front 16

displays the distribution of a qualitative variable by dividing a circle into wedges corresponding to
the percentage of items in that category

Back 16

pie chart

Front 17

displays the distribution of a qualitative variable by listing the categories of the variable along one
axis and drawing a bar over each category with a height (or length) equal to the percentage of items in that category

Back 17

bar graph

Front 18

Two types of Qualitative Variables?

Back 18

1. Nominal
2. Ordinal

Front 19

Two Types of Quantitative Variables?

Back 19

1. Discrete
2. Continuous

Front 20

How many equally spaced intervals are good for a histogram?

Back 20

between 6 to 15

Front 21

count

Back 21

frequencies

Front 22

proportion

Back 22

relative frequencies

Front 23

displays a dot for each observation along a number line

Back 23

dotplot

Front 24

contains all but the last of the displayed digits of a number

Back 24

stem

Front 25

the last of the displayed digits of a number

Back 25

leaf

Front 26

Two things to look for in any graph of data?

Back 26

Overall pattern and for striking deviations from that pattern

Front 27

Three things that describe the overall pattern?

Back 27

Shape, center, and spread

Front 28

an individual value that falls outside the overall pattern

Back 28

outlier

Front 29

if the right and left sides of the histogram are approximately mirror images of each other

Back 29

symmetric

Front 30

if the right side of the histogram (containing the half of the observations with the larger values) extends much farther out than the left side

Back 30

skewed to the right

Front 31

if the left side of the histogram extends much farther out than the right side

Back 31

skewed to the left

Front 32

Normal shape of distribution?

Back 32

Symmetric, bell-shaped, unimodal

Front 33

plots each observation against the time at which it was measured

Back 33

time plot

Front 34

What does a time plot help determine?

Back 34

Whether a distribution is changing over time

Front 35

average value in a data set

Back 35

mean

Front 36

midpoint of a distribution

Back 36

median

Front 37

Because the mean cannot resist the influence of extreme observations, we say that it is?

Back 37

not a resistant measure of center

Front 38

The median is this to extreme observations?

Back 38

resistant

Front 39

The mean and median of a symmetric distribution are?

Back 39

exactly the same

Front 40

The simplest useful numerical description of a distribution consists of?

Back 40

both a measure of center and a measure of spread

Front 41

high value - low value

Back 41

range

Front 42

upper quartile - lower quartile

Back 42

interquartile range (IQR)

Front 43

median of data values that are below the median

Back 43

lower quartile

Front 44

median of data values that are above the median

Back 44

upper quartile

Front 45

the median of the observations whose position in the ordered list is to the left of the location of the overall median

Back 45

lower quartile Q1

Front 46

the median of the observations whose position in the ordered list is to the right of the location of the overall median

Back 46

upper quartile Q3

Front 47

consists of the smallest observation, the first quartile, the median, the third quartile, and the largest observation, written in order from smallest to largest

Back 47

five-number summary

Front 48

a number that has k% of the data values at or below it and (100-k)% of the data values at or above it

Back 48

k^th percentile

Front 49

In a dataplot, points represented by asterisks are considered to be?

Back 49

outliers

Front 50

Q3 - Q1

Back 50

interquartile range

Front 51

Are fences sketched on a boxplot?

Back 51

No