Statistics Chapter 1

Front 1

Using a vertical scale that doesn't start at zero

Back 1

Exaggerate the difference between the two numbers of responses

Front 2

Voluntary response (self-selected) sample

Back 2

Respondents decide themselves whether to participate

Hint 2

Those with the strong interest in the topic or more likely to participate so results are very questionable

Front 3

It is important to obtain sample data

Back 3

That are representative of the population from which the data are shown

Front 4

Small samples

Back 4

Conclusion should not be based on samples that are far too small

Front 5

Sample data must be collected

Back 5

In an appropriate way such as through a process of random selection

Front 6

If sample data are not collected in an appropriate way

Back 6

The data may be so completely useless that no amount of statistical torturing can salvage them

Front 7

Data

Back 7

Collections of observations such as measurements genders or survey responses

Front 8

A single data value

Back 8

Datum

Front 9

Statistics

Back 9

The science of planning studies and experiments obtaining data and then organizing summarizing presenting analyzing and interpreting those data and then drawing conclusions based on them

Front 10

Population

Back 10

The complete collection of all measurements or data that are being considered

Front 11

Census

Back 11

The collection of data from every member of the population

Front 12

Sample

Back 12

A subcollection of members selected from a population

Front 13

Statistical study

Back 13

Prepare analyze and conclude

Front 14

Prepare

Back 14

Context

source of the data

sampling method

Front 15

Analyze

Back 15

Graph the data

Explore the data

Apply statistical methods

Front 16

Conclude

Back 16

Statistical significance

Front 17

Statistical significance

Back 17

Results not likely to happen by chance

Front 18

Practical significance

Back 18

Looks at whether the difference is large enough to be a value in a practical sense

Hint 18

For example if participants in the Atkins diet lost two pounds a year there is statistical significance but not practical

Front 19

Value of a statistical life (VSL)

Back 19

The amount of money a person or Society is willing to spend to save a life

Hint 19

Since there is no formal market for lives the only way to measure the vsl is through indirect methods, for example surveys or observed human behavior in risky environments

Front 20

Common examples of voluntary response samples

Back 20

Internet polls in which people online can decide whether to respond

Mail-in polls in which subject can decide whether to reply

Telephone call-in polls in which newspaper radio or television announcements can ask that you voluntarily call a special number to register your opinion

Front 21

What is incorrectly use to assert or imply conclusions about a larger population?

Back 21

Voluntary response samples

Hint 21

Such a sample is fundamentally flawed and should not be used for making a general statement about a larger population

Front 22

Publication bias

Back 22

The tendency to publish positive results (such as showing that some treatment is effective) much more often the negative results

Front 23

Graph such as bar graphs and pie charts can

Back 23

Be used to exaggerate or understate the true nature of data

Front 24

Pictographs

Back 24

Drawing of objects

Hint 24

Can also be misleading

Front 25

Misleading or unclear percentages

Back 25

Are sometimes used

If you are taking 100% of some quantity you are taking it all

Front 26

It is not necessarily the size of the sample that makes it effective

Back 26

But the sampling method does

Front 27

Benford's law

Back 27

An observation about the frequency distribution of leading digits in many real life sets of numerical data

Hint 27

The law states that in many naturally occurring collections of numbers deleting significant digit is likely to be small

Front 28

Correlation

Back 28

Association between two variables

Correlation does not imply causation

Hint 28

For example smoking and pulse rate

Front 29

Loaded questions

Back 29

If survey questions are not worded carefully the results of a study can be misleading

Front 30

Order of questions

Back 30

Sometimes survey questions are unintentionally loaded by such factors as the order of the items being considered

Front 31

Non-response

Back 31

Occurs when someone either refuses to respond to a survey question or is unavailable

Front 32

Sugging

Back 32

Mini telemarketers trying to sell goods or services by beginning with a sales pitch that intentionally sounds like it is part of an opinion

Front 33

Results can sometimes be dramatically affected by

Back 33

Missing data

Front 34

Precise numbers

Back 34

Because that figure is precise many people incorrectly assume that it is also accurate

Front 35

To find a percentage of an amount

Back 35

Drop the percent symbol and then divide the % value by 100 then multiply

Front 36

Parameter

Back 36

A numerical measurement describing some characteristic of a population

Front 37

Statistic

Back 37

A numerical measurement describing some characteristic of a sample

Front 38

Quantitative or numerical data

Back 38

Consists of numbers representing counts or measurements

Front 39

Categorical or qualitative or attribute data

Back 39

Consist of names or labels that are not numbers representing counts or measurements

Front 40

In a survey of 521 subjects each was asked how often he or she played Sports. The survey subjects were internet users who responded to a question that was posted on a News website.

Back 40

It is flawed because it is a voluntary response sample.

Front 41

In a survey of 614 human resource professionals, each was asked about the importance of the appearance of a job applicant. The survey subjects are randomly selected by posters from a reputable market research firm.

Back 41

It appears to be sad because the data are not biased in any way.

Front 42

Quantitative or numerical data example

Back 42

The ages in years of survey respondents

Front 43

Categorical data as labels

Back 43

Categorical data as labels: the political party affiliations of survey respondents for example Democrat Republican independent

Front 44

Categorical data as numbers

Back 44

The numbers 12, 47, 75, 88, and 25 were soon on the jerseys of the starting offense for the New Orleans Saints when they won a recent Super Bowl. Those numbers are substitutes for names. They don't measure or count anything, so they are categorical data.

Front 45

Quantitative data can be further described by

Back 45

Distinguishing between discrete and continuous types.

Front 46

Discrete data

Back 46

Finite values, or buckets

Number of children in household.

Number of languages a person speaks.

Number of people sleeping in stats class.

Hint 46

If there are infinitely many values, the collection of values is countable if it is possible to count them individually, such as the number of tosses of a coin before getting tails.

Front 47

Continuous numerical data

Back 47

Result from infinitely many possible quantitative values, where the collection of values is not countable.

Hint 47

Height of children

Weight of cars

Time to wake up in the morning

Speed of the train

Front 48

Discrete data of the finite type

Back 48

The number of eggs that hens lay in one week or discrete data because they are finite numbers, such as five and seven that result from a counting process.

Front 49

Discrete data of the infinite type

Back 49

Consider the number of rolls of a die required to get an outcome of 2. It is possible that you could roll a die forever without getting a 2, but you can still count the number of rolls as you proceed. The collection of rolls is countable, because you can count them, even though you might go on Counting forever.

Front 50

Continuous data

Back 50

During the year, account might yield amount of milk that can be of any value between 0 liters and 7000 liters. There are infinitely many values between 0 liters and 7000 liters, but it is impossible to count the number of different possible values on such a continuous scale.

Front 51

The numbers of cans of cola are discrete data

Back 51

Correct grammar dictates that we use fewer for discrete amounts.