Question 1

is the science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions. is a numerical summary based on a sample.

Accepted Answer

Statistics

Question 2

fact or proposition used to draw 
a conclusion or make a decision.

Accepted Answer

Data

Question 3

The entire group of individuals to be studied.

Accepted Answer

population

Question 4

a person or object that is a member of the population being studied.

Accepted Answer

individual

Question 5

a subset of the population that is being studied. is a statistic.

Accepted Answer

sample

Question 6

consist of organizing and summarizing data. describe data through numerical summaries, tables, and graphs.

Accepted Answer

Descriptive statistics

Question 7

uses methods that take results from a sample, extends them 
to the population and measures the reliability of the result.

Accepted Answer

Inferential statistics

Question 8

a numerical summary of a population. population mean.

Accepted Answer

parameter

Question 9

are the characteristics of the individuals within the population.

Accepted Answer

Variables

Question 10

allow for classification of individuals based on some 
attribute or characteristic.

Accepted Answer

Qualitative, or categorical, variables

Question 11

provide numerical measures of individuals. its values can be added or subtracted and provide meaningful results.

Accepted Answer

Quantitative variables

Question 12

is a quantitative variable that has either a finite number of possible values or 
a countable number of possible values.

Accepted Answer

discrete variable

Question 13

means that the values result from 
counting, such as 0, 1, 2, 3 and so on.

Accepted Answer

countable

Question 14

is a quantitative variable that has an infinite number of possible values 
that are not countable.

Accepted Answer

continuous variable

Question 15

is a list of all individuals in a population along with certain characteristics of each 
individual.

Accepted Answer

census

Question 16

is the process of using chance to select individuals from a population to be 
included in the sample.

Accepted Answer

Random sampling

Question 17

every possible sample has an equally likely chance of occurring.

Accepted Answer

Simple Random Sampling

Question 18

n

Accepted Answer

sample size

Question 19

N

Accepted Answer

population size

Question 20

is obtained by separating the population into nonoverlapping groups called strata and then obtaining a simple random sample from each stratum.

Accepted Answer

stratified sample

Question 21

is obtained by selecting every kth individual from the population.

Accepted Answer

systematic sample

Question 22

is obtained by selecting all individuals within a randomly selected collection or 
group of individuals.

Accepted Answer

cluster sample

Question 23

is a sample in which the individuals are easily obtained and not based on randomness.

Accepted Answer

convenience sample

Question 24

Data that is not organized

Accepted Answer

raw data

Question 25

lists each category of data and the number of occurrences for each category of data.

Accepted Answer

frequency distribution

Question 26

is the proportion (or percent) of observations within a category.

Accepted Answer

relative frequency

Question 27

lists each category of data together with the relative frequency.

Accepted Answer

relative frequency distribution

Question 28

is constructed by labeling each category of data on either the horizontal or vertical axis and the frequency or relative frequency of the category on the other axis.

Accepted Answer

bar graph

Question 29

is a bar graph whose bars are drawn in decreasing order of frequency or relative frequency.

Accepted Answer

Pareto chart

Question 30

is a circle divided into sectors. Each sector represents a category of data.    (relative freq. times 360degrees)

Accepted Answer

pie chart

Question 31

1st step to quantitative you must know of it's.

Accepted Answer

discrete or continuous

Question 32

with relatively few different values of the variable, then the categories of data (called classes) will be the observations (as in qualitative data).

Accepted Answer

descrete

Question 33

but with many different values of the variable or if the data are continuous, then categories of data (classes) must be created using intervals of numbers.

Accepted Answer

discrete

Question 34

is constructed by drawing rectangles for each class of data. The height of each rectangle is the frequency or relative frequency of the class. The width of each rectangle is the 
same and the rectangles touch each other.

Accepted Answer

histogram

Question 35

are categories into which data are grouped.

Accepted Answer

Classes

Question 36

is the smallest value within the class.

Accepted Answer

lower class limit

Question 37

is the largest value within the class.

Accepted Answer

upper class limit

Question 38

is the difference between consecutive lower-class limits. (works just the same as higher-class limits.)

Accepted Answer

class width

Question 39

is another way to represent quantitative data graphically.  use the digits to the left of the rightmost digit to form the stem. Each rightmost digit forms a leaf.

Accepted Answer

stem-and-leaf plot

Question 40

the frequency of each value of the variable is evenly spread out across the values of the variable.

Accepted Answer

Uniform distribution

Question 41

the highest frequency occurs in the middle and frequencies tail off to the left and right of the middle.

Accepted Answer

Bell-shaped distribution

Question 42

the tail to the right of the peak is longer than the tail to the left of the peak.

Accepted Answer

Skewed right

Question 43

the tail to the left of the peak is longer than the tail to the right of the peak.

Accepted Answer

Skewed left

Question 44

is the sum of consecutive lower class limits divided by 2.

Accepted Answer

class midpoint

Question 45

displays the aggregate frequency of the category. In other words, for discrete data, it displays the total number of observations less than or equal to the category.

Accepted Answer

cumulative frequency distribution

Question 46

displays the proportion (or percentage) of observations less than or equal to the category for discrete data and the proportion (or percentage) of observations less than or equal to the upper class limit of a class for continuous data.

Accepted Answer

cumulative relative frequency distribution

Question 47

is computed by adding all the values of the variable in the 
data set and dividing by the number of observations.

Accepted Answer

arithmetic mean

Question 48

(pronounced “mew”), is computed using all the individuals in a population.

Accepted Answer

population arithmetic mean, µ

Question 49

(pronounced “x-bar”), is computed using sample data. The 
sample mean is a statistic.

Accepted Answer

sample arithmetic mean, (x with a line on it)

Question 50

is the value that lies in the middle of the data when arranged in 
ascending order. represents M.

Accepted Answer

median

Question 51

is the most frequent observation of the variable that occurs in the data set.

Accepted Answer

mode

Question 52

____and_____need numerical, but_____can use numerical and categorical.

Accepted Answer

mean and median, mode

Question 53

is the difference between the largest and the smallest data value.

Accepted Answer

range, R

Question 54

is the square root of the sum of squared deviations about the population mean divided by the number of observations in the population, N. That is, it is the square root of the mean of the squared deviations about the population mean.

Accepted Answer

population standard deviation

Question 55

is the square root of the sum of squared deviations about the sample mean divided by n – 1, where n is the sample size.

Accepted Answer

sample standard deviation, s

Question 56

is the square of the standard deviation.

Accepted Answer

variance

Question 57

𝜎 squared

Accepted Answer

population variance

Question 58

𝑠 squared

Accepted Answer

sample variance

Question 59

68% lie within 1 STDEV of the mean.  𝜇−1𝜎 and 𝜇+1𝜎
95% lie within 2 STDEV of the mean. 𝜇−2𝜎 and 𝜇+2𝜎
99.7% lie within 3 STDEV of the mean. 𝜇−3𝜎 and 𝜇+3𝜎

Accepted Answer

The Empirical Rule

Question 60

of a variable is found by multiplying each value of the variable by its corresponding weight, adding these products, and dividing this sum by the sum of the weights.

Accepted Answer

weighted mean, "x var" with bottom corner "w."

Question 61

represents the distance that a data value is from the mean in terms of the number of standard deviations. We find it by subtracting the mean from the data value and dividing this result by the standard deviation.

Accepted Answer

z-score

Question 62

denoted 𝑃 "with bottom corner k", of a set of data is a value such that k percent of the observations 
are less than or equal to the value.

Accepted Answer

kth percentile

Question 63

divide data sets into fourths, or four equal parts.

Accepted Answer

Quartiles

Question 64

denoted 𝑄1, divides the bottom 25% of the data from the top 75%.

Accepted Answer

first quartile

Question	Answer
is the science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions. is a numerical summary based on a sample.	Statistics
fact or proposition used to draw a conclusion or make a decision.	Data
The entire group of individuals to be studied.	population
a person or object that is a member of the population being studied.	individual
a subset of the population that is being studied. is a statistic.	sample
consist of organizing and summarizing data. describe data through numerical summaries, tables, and graphs.	Descriptive statistics
uses methods that take results from a sample, extends them to the population and measures the reliability of the result.	Inferential statistics
a numerical summary of a population. population mean.	parameter
are the characteristics of the individuals within the population.	Variables
allow for classification of individuals based on some attribute or characteristic.	Qualitative, or categorical, variables
provide numerical measures of individuals. its values can be added or subtracted and provide meaningful results.	Quantitative variables
is a quantitative variable that has either a finite number of possible values or a countable number of possible values.	discrete variable
means that the values result from counting, such as 0, 1, 2, 3 and so on.	countable
is a quantitative variable that has an infinite number of possible values that are not countable.	continuous variable
is a list of all individuals in a population along with certain characteristics of each individual.	census
is the process of using chance to select individuals from a population to be included in the sample.	Random sampling
every possible sample has an equally likely chance of occurring.	Simple Random Sampling
n	sample size
N	population size
is obtained by separating the population into nonoverlapping groups called strata and then obtaining a simple random sample from each stratum.	stratified sample
is obtained by selecting every kth individual from the population.	systematic sample
is obtained by selecting all individuals within a randomly selected collection or group of individuals.	cluster sample
is a sample in which the individuals are easily obtained and not based on randomness.	convenience sample
Data that is not organized	raw data
lists each category of data and the number of occurrences for each category of data.	frequency distribution
is the proportion (or percent) of observations within a category.	relative frequency
lists each category of data together with the relative frequency.	relative frequency distribution
is constructed by labeling each category of data on either the horizontal or vertical axis and the frequency or relative frequency of the category on the other axis.	bar graph
is a bar graph whose bars are drawn in decreasing order of frequency or relative frequency.	Pareto chart
is a circle divided into sectors. Each sector represents a category of data. (relative freq. times 360degrees)	pie chart
1st step to quantitative you must know of it's.	discrete or continuous
with relatively few different values of the variable, then the categories of data (called classes) will be the observations (as in qualitative data).	descrete
but with many different values of the variable or if the data are continuous, then categories of data (classes) must be created using intervals of numbers.	discrete
is constructed by drawing rectangles for each class of data. The height of each rectangle is the frequency or relative frequency of the class. The width of each rectangle is the same and the rectangles touch each other.	histogram
are categories into which data are grouped.	Classes
is the smallest value within the class.	lower class limit
is the largest value within the class.	upper class limit
is the difference between consecutive lower-class limits. (works just the same as higher-class limits.)	class width
is another way to represent quantitative data graphically. use the digits to the left of the rightmost digit to form the stem. Each rightmost digit forms a leaf.	stem-and-leaf plot
the frequency of each value of the variable is evenly spread out across the values of the variable.	Uniform distribution
the highest frequency occurs in the middle and frequencies tail off to the left and right of the middle.	Bell-shaped distribution
the tail to the right of the peak is longer than the tail to the left of the peak.	Skewed right
the tail to the left of the peak is longer than the tail to the right of the peak.	Skewed left
is the sum of consecutive lower class limits divided by 2.	class midpoint
displays the aggregate frequency of the category. In other words, for discrete data, it displays the total number of observations less than or equal to the category.	cumulative frequency distribution
displays the proportion (or percentage) of observations less than or equal to the category for discrete data and the proportion (or percentage) of observations less than or equal to the upper class limit of a class for continuous data.	cumulative relative frequency distribution
is computed by adding all the values of the variable in the data set and dividing by the number of observations.	arithmetic mean
(pronounced “mew”), is computed using all the individuals in a population.	population arithmetic mean, µ
(pronounced “x-bar”), is computed using sample data. The sample mean is a statistic.	sample arithmetic mean, (x with a line on it)
is the value that lies in the middle of the data when arranged in ascending order. represents M.	median
is the most frequent observation of the variable that occurs in the data set.	mode
____and_____need numerical, but_____can use numerical and categorical.	mean and median, mode
is the difference between the largest and the smallest data value.	range, R
is the square root of the sum of squared deviations about the population mean divided by the number of observations in the population, N. That is, it is the square root of the mean of the squared deviations about the population mean.	population standard deviation
is the square root of the sum of squared deviations about the sample mean divided by n – 1, where n is the sample size.	sample standard deviation, s
is the square of the standard deviation.	variance
𝜎 squared	population variance
𝑠 squared	sample variance
68% lie within 1 STDEV of the mean. 𝜇−1𝜎 and 𝜇+1𝜎 95% lie within 2 STDEV of the mean. 𝜇−2𝜎 and 𝜇+2𝜎 99.7% lie within 3 STDEV of the mean. 𝜇−3𝜎 and 𝜇+3𝜎	The Empirical Rule
of a variable is found by multiplying each value of the variable by its corresponding weight, adding these products, and dividing this sum by the sum of the weights.	weighted mean, "x var" with bottom corner "w."
represents the distance that a data value is from the mean in terms of the number of standard deviations. We find it by subtracting the mean from the data value and dividing this result by the standard deviation.	z-score
denoted 𝑃 "with bottom corner k", of a set of data is a value such that k percent of the observations are less than or equal to the value.	kth percentile
divide data sets into fourths, or four equal parts.	Quartiles
denoted 𝑄1, divides the bottom 25% of the data from the top 75%.	first quartile
Q2, divides the bottom 50% of the data from the top 50%; it is equivalent to the 50th percentile or the median.	second quartile
𝑄3, divides the bottom 75% of the data from the top 25%; it is equivalent to the 75th percentile.	third quartile
is the range of the middle 50% of the observations in a data set.	interquartile range, IQR
Shape of Distribution and Measure of Central Tendency. Symmetric, Mean	standard deviation
Shape of Distribution and Measure of Central Tendency. Skewed left or skewed right, Median	interquartile range
Extreme observations	outliers
serve as cutoff points for determining outliers.	Fences
Minimum, Q1, M, Q3, Maximum	Five-Number Summary
know how to draw a box plot	know how to draw a box plot

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stats ch 1-3