Statistics Chapter 1

Front 1

Data

Back 1

are observations (such as measurements, genders, survey responses) that have been collected

Front 2

Statistics

Back 2

Is a collection of methods for planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data.

Front 3

Population

Back 3

Is the complete collection of all elements (scores, people, measurements, and so on) to be studied. The collection is complete in the sense that it includes all subjects to be studied

Front 4

Cenus

Back 4

Is the collection of data from ever member of the population

Front 5

Sample

Back 5

is a sub collection of members selected from a population

Front 6

Parameter

Back 6

Is a numerical measurement describing some characteristic of a population
In New York City, there are 3250 walk buttons that pedestrians can press at traffic intersections. It was found that 77% of those buttons do not work (based on data from the article "For Exercise in New York Futility, Push Button" by Michael Luo, New York Times). The firgure of 77% is a parameter because it is based on the entire population of all 3250 pedestrian push buttons

Front 7

Statistics

Back 7

Based on a sample of 877 surveyed executives, it is found that 45% of them would not hire someone with a typographic error on their job application. That figure 45% statistic because it is based on a sample, not the entire population of all executives.

Front 8

Quantitative data

Back 8

Consist of numbers representing counts or measurements
The weights of supermodels

Front 9

Qualitative data

Back 9

Can be seperated into different categories that are distinguished by some nonnumeric characteristic
The genders of professional athletes

Front 10

Discrete data

Back 10

Results when the number of possible values is either a finite number or a "countable" number. (That is, the number of possible values is 0 or 1 or 2 and so on.)
The number of eggs that hens lay are discrete data because they represent counts

Front 11

Continuous data

Back 11

Results from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interuptions, or jumps.
The amounts of milk from cows are continuous data because they are measurements that can assume any value over a continuous span

Front 12

Nominal Level of Measurement

Back 12

Characterized by data that consist of names, labels, or categories only. The data cannot be arranged in an ordering scheme (such as low to high).
Yes/no/undecided: survery responses of yes, no and undecided
Colors: The colors of cars driven by college students (red, black, blue, white, magenta, mauve, and so on)

Front 13

Ordinal Level of Measurement

Back 13

They can be arranged in some order, but differences between data values either cannot be determined or are meaningless
Course Grades: A college professor assigns grades of A, B, C, D, F
Ranks: Magazine ranks cities according to their "livability" Those ranks (first, second, third, and so on) determine an ordering.

Front 14

Interval Level of Measurement

Back 14

Like the ordinal level, with the additional property that the difference between any two data balues is meaningful. However,data at this level do not have a natural zero starting point (where none of the quantity is present)
Temperatures: There are no natural startying point. The value deg F might seem like a starting point, but it is arbitrary
Years: Time does not begin in the year zero, so the year zero is arbitrary instead of being a natural zero starting point representing "no time"

Front 15

Ratio Level of Measurement

Back 15

Is the interval Level with the addition property that there is also a natural zero starting point (where zero indicates that none of the quantity is present). For values at this level, differences and ratios are both meaningful
Weights: Weights (in carats) of diamond engagement rings
Prices: prices of college textvooks (0$ does represent no cost, and a 90$ book is three times as costly as a $30 book).

Front 16

Voluntary Response Sample/ Self-reflected Sample

Back 16

Is one in which the respondents themselves decide whether to be included

Front 17

Small Samples

Back 17

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

Front 18

Graphs

Back 18

Graphs-such as bar grapghs and pie charts can be used to exaggerate or understate the true nature of data

Front 19

Pictographs

Back 19

Drawing of objects, called pictographs, may also be misleading. SOme objects commonly used to depict data inclue three-dimensional objects. When drawing such objects, artist can create false impressions that distort diffwerences.

Front 20

Percentages

Back 20

Misleading or unclear percentages are sometimes used. If you take 100% of some quantity, you are taking it all. ( It shouldnt require 110% effort to make sense of the preceding statement)

Front 21

Loaded Questions

Back 21

There are many iussues affecting survey questions. Survey Questions can be loaded or intentionally worded to elicit a desired response

Front 22

Order of Questions

Back 22

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

Front 23

Nonresponse.

Back 23

A nonresponse occurs when someone either refuses to respond to a survey question, or the person is unavailable.

Front 24

Missing data

Back 24

Results can sometimes be dramatically affected by missing data

Front 25

Correlation and Causality

Back 25

Correlkation does not implu causality

Front 26

Self-Intrest Study

Back 26

Studies are sometimes sponsored by parties with intresent to promote

Front 27

Precise Numbers

Back 27

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

Front 28

Deliberate Distortions

Back 28

False advertising based on a survey

Front 29

Observational Study

Back 29

We pbserve and measure specific characteristics, but we don't attempt to modify the subjects being studied

Front 30

Experiment

Back 30

We apply some treatement and then process to observe its effect on the subjects ( subjects in experiments are called experimental units)

Front 31

Cross-sectional study

Back 31

Data are observed, measured, and collected at one point in time

Front 32

Retrospective (case-control) study

Back 32

Data are collected from the past by going back in time (through examination of records, interviews, and so on).

Front 33

Prospective (longitudinal/cohort) study

Back 33

Data are collected in the future from groups sharing common factos

Front 34

Confounding

Back 34

Occurs in an experiment when you are not able to difstinguish among the effects of different factors

Front 35

Placebo effect

Back 35

Occurs when an untreated subjects reports an improvement in sumptoms

Front 36

Blinding

Back 36

a technique in which the subject doesn't know whether he or she is receiving a treatement or a placebo

Front 37

Double blind

Back 37

Means the blinding occured at 2 levels
(1) The children being injected didn't know whether they were getting the treatement or placebo (2) the doctors who gave the injections and evaluated the results did not know either

Front 38

Block

Back 38

Is a group of subjects that are similar

Front 39

Completely Randomized Experimental Design

Back 39

Subjects are assigned to different treatment groups through a process of random selection

Front 40

Rigorously Controlled Design

Back 40

In which subjects are very carefully chosen so that those given each treatment are similar in the ways that are important to the experiment

Front 41

Replication

Back 41

Repetition of an experiment on sufficiently large groups of subjects is called replication, and replication is used effectiveluy when we have enough subjects to recognize difference from different treatment

Front 42

Random Sample

Back 42

Members from the population are selected in such a way that each individual member has an equal chance of being selected

Front 43

Simple random sample

Back 43

of n subjects is selected in such a way that ever possible sample of the same size n has the same chance of being chosen

Front 44

Probability sample

Back 44

involves selecting members from a population in suh a way that each member has a known (but not necessarily the same) chance of being selected

Front 45

Systematic Sampling

Back 45

We select some starting point and then select every kth element in the population

Front 46

Convenience sampling

Back 46

We simply use results that are very easy to get

Front 47

Stratified Sample

Back 47

We subdividing the population into at least 2 different subgroups so that subjects within the same subgroup share the same characteristics then we draw a sample from each subgroup

Front 48

Cluster sampling

Back 48

we first divide the population area into sections then randomly select some of those clusters and then choose all the members from those selected clusters

Front 49

Multistage sample

Back 49

involves the selection of a sample in different stages that might use different methods of sampling

Front 50

Sampling Error

Back 50

Is the difference between a sample result and the true population result; such an error results from chance sample fluctuations

Front 51

Nonsampling Error

Back 51

Occurs when the sample data are incorrectly collected, recorded, or analyzed