Statistics Unit 1

Front 1

A subset of the population that is being studied

Back 1

Sample

Front 2

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

Back 2

Individual

Front 3

Characteristics of the individuals within the population

Back 3

Data/variables

Front 4

Numerical summary of a population

Back 4

Parameter

Front 5

Numerical summary of a sample

Back 5

Statistic

Front 6

Type of statistics that consists of organizing and summarizing data and describes data through numerical summaries, tables, and graphs

Back 6

Descriptive statistics

Front 7

Type of statistics that uses methods that take a result from a sample, extends it to the population, and measures the reliability of the result

Back 7

Inferential statistics

Front 8

Type of data/variable which classifies individuals based on some attribute or characteristic: identification

Back 8

Qualitative variables

Front 9

Type of data/variable that provides numerical measures for individuals. Arithmetic operations can be performed on these values and provide meaningful results

Back 9

Quantitative variables

Front 10

Type of quantitative data that is countable and finite

Back 10

Discrete

Front 11

Type of quantitative data that is measured

Back 11

Continuous

Front 12

Process of using chance to select individuals from a population to be included in the sample; equally likely

Back 12

Simple random sampling

Front 13

Type of sampling obtained by separating the population into nonoverlapping groups called strata and then obtaining a simple random sample from each stratum. The individuals within each stratum (group) should be similar in some way

Back 13

Stratified sample

Front 14

Type of sampling obtained by selecting every kth individual from the population. The first individual selected corresponds to a random number between 1 and k; spreads out the sample to increase randomness

Back 14

Systematic sampling

Front 15

Sampling obtained by selecting all individuals within a randomly selected collection or group of individuals. Groups do not have to be similar

Back 15

Cluster sampling

Front 16

Sample in which individuals are easily obtained and not based on randomness

Back 16

Convenience sampling

Front 17

Lists each category of data and the number of occurrences for each category of data

Back 17

Frequency distribution

Front 18

The proportion of observations within a category

Back 18

Relative frequency

Front 19

Lists each category of data together with the relative frequency

Back 19

Relative frequency distribution

Front 20

Categories of data

Back 20

Classes

Front 21

The ____ of a class is the smallest value within the class

Back 21

Lower class limit

Front 22

The ____ of a class is the largest value within a class

Back 22

Upper class limit

Front 23

The ____ is the difference between consecutive lower class limits

Back 23

Class width

Front 24

The three measures of spread

Back 24

Range, variance, standard deviation

Front 25

The three measures of center

Back 25

Mean, median, mode

Front 26

The empirical rule

Back 26

68, 95, 99.7

Front 27

A histogram or table is an example of (descriptive or inferential) statistics

Back 27

Descriptive

Front 28

One can make reasonable guesses using (descriptive or inferential) statistics

Back 28

Inferential

Front 29

List of all possible outcomes

Back 29

Distribution

Front 30

___ distribution is when the frequency of the values is spread evenly

Back 30

Uniform (symmetric)

Hint 30

Front 31

___ distribution is when the highest frequency occurs in the middle and frequencies tail off the left and right

Back 31

Bell-shaped (symmetric)

Hint 31

Front 32

Is money discrete or continuous?

Back 32

Discrete because it's countable

Front 33

Symbol for population mean

Back 33

Mew

Front 34

Symbol for population size

Back 34

N

Front 35

Symbol for sample mean

Back 35

X bar

Front 36

Symbol for sample size

Back 36

n

Front 37

The measure of center that divides data in half

Back 37

Median

Front 38

How to find median of even numbered data set

Back 38

Take the mean of the middle two numbers

Front 39

Relationship of mean and median when distribution is skewed left

Back 39

Mean < median

Front 40

Relationship of mean and median when distribution is skewed right

Back 40

Mean > median

Front 41

Shape of distribution when mean=median

Back 41

Symmetric

Front 42

The measure of spread best used to describe skewed data

Back 42

Median

Front 43

True or false: an observation is the mode just because it repeats.

Back 43

False: the mode is an observation that occurs the MOST

Front 44

Phrase indicative of a sample instead of a population

Back 44

Randomly selected

Front 45

The sum of all deviation about the mean usually equals ___, so finding the deviation mean this way would be impossible. How is this solved?

Back 45

Zero. By taking the average of the SQUARED deviations (variance)

Front 46

How do you find the standard deviation?

Back 46

By taking the square root of the variance

Front 47

The sum of the squared deviations

Back 47

Variance

Front 48

Average deviation about the mean

Back 48

Standard deviation

Front 49

Empirical rule

Back 49

68-95-99.7 rule helps summarize and describe data set

Front 50

Term for data lying outside of two standard deviations from the mean

Back 50

Unusual

Front 51

Z score Formula

Back 51

X - mean/standard deviation

Front 52

Population variance formula

Back 52

Sum of all deviations squared/N

Front 53

Sample variance formula

Back 53

Sum of all deviations squared / n-1

Front 54

Symbol for population standard deviation

Back 54

Sigma

Front 55

Symbol for population standard deviation

Back 55

Sigma

Front 56

Symbol for sample standard deviation

Back 56

S