algonquin college - janet ladas1 community dental health

Algonquin College - Janet Ladas 1

COMMUNITY DENTAL HEALTHCOMMUNITY DENTAL HEALTH


STATISTICSSTATISTICS

Statistics is the field of study which concerns itself with the art and science of data analysis:

• Planning, collecting, organizing, analyzing, interpreting, summarizing and presenting the data

Statistics, when used in the plural form, refers to the specific bits of data which either have been or are about to be gathered.


STATISTICSSTATISTICS

Foreign Language:• Special meaning for words like mean, regression,

normal, confidence, correlation, population, discrete, conditional, union, posterior, hypothesis etc., etc., etc.

Logic related to statistics more than math. (H.S. Algebra) – computers

* Complex and demanding subject area


INTRODUCTION TO INTRODUCTION TO BIOSTATISTICSBIOSTATISTICS

Biostatistics:The mathematics of collection, organization

and interpretation of numeric data having to do with living organisms.

Techniques to manage data:• Descriptive• Inferential


INTRODUCTION TO INTRODUCTION TO BIOSTATISTICSBIOSTATISTICS

Uses for data: (To name a few)

• Designing a health care program or facility

• Evaluating the effectiveness of an ongoing program

• Determining needs of a specific population

• Evaluating the accuracy of a journal article


EPIDEMIOLOGYEPIDEMIOLOGY

The scientific study of factors that influence the frequency and distribution of disease in a population.


METHODS OF MEASURING METHODS OF MEASURING ORAL DISEASEORAL DISEASE

Counts:• A simple number of cases of occurrence• Useful when there is a low prevalence

e.g. 12 cases of oral cancer

Proportions:• A count can be turned into a proportion by adding a

denominator thus determining prevalencee.g. 12 cases in a population of 1,500 students

• Does not include a time dimension thus includes new cases as well as longstanding ones



Rates:• A proportion that uses a standardized denominator

and includes a time dimension

Types of Rates: (As applied to Biostatistics)

Morbidity Rate:• The proportion of people ill with the disease over a

specified time span

formula: # of new cases /100,000 people / year

e.g.: 12 / 1,500 / 2000



Mortality Rate:• The proportion of people who die from the disease during a

period of time

formula: # of deaths / 100,000 people / year

e.g.: 8 / 1,500 / 2000

Case Rate:• Frequency of occurrence of the condition / disease

formula: # of occurrences / # of births / year

e.g.: 1 / 700 / 2001 (Cleft Palatte Cases)

n.b. rates can be converted into percentages


INDEXES (INDICES)INDEXES (INDICES)

An index is a measure of quantification of epidemiological data

• A numerical value on a graduated scale• Scores correspond to specific criteria• Have definite upper and lower limitsExamples:• DMFT’s – caries activity – best known –

irreversible• RCI – root caries - irreversible


INDEXES (INDICES)INDEXES (INDICES)

• GBI – Gingival Bleeding – reversible• CPITN – Community Periodontal Index of

Treatment Needs• DFI – Dental FluorosisNote:• No generic, all purpose scale• Depends on the reason for using that measure,

how to handle it reliably and what you want to demonstrate


DENTAL HEALTH INDICESDENTAL HEALTH INDICES

Dental conditions readily lend themselves to study because we have specific tools for speed and accuracy of measurement.

Index Properties• Clear, simple, objective• Valid – measures what it is supposed to• Reliable – consistent on repetition• Quantifiable – data can be analyzed• Sensitive – can detect small shifts in either direction• Acceptable – not painful or demeaning to the subject• Clinically significant and meaningful


CARIES ACTIVITIES INDICESCARIES ACTIVITIES INDICES

DMFT : decayed, missing, filled permanent teethdeft : primary teeth• Each tooth must have a score but only one (DMF or sound)• Recurrent caries = decayed (D)• Missing teeth = extracted or due to be extracted due to caries• Teeth not deemed as missing = unerupted, congenitally absent,

accidentally lost or extracted for ortho. Purpose• Third molars not scored

DMFT and deft scores are objective thus require high agreement between examiners.

DMFS and defs (surfaces) are more subjective thus less reliable.


FACTS ABOUT DATAFACTS ABOUT DATATwo types of data:Qualitative: labels used to identify an item when it cannot

be numerically identified.e.g.: marital status, car colour, occupation

(attributes)n.b.: has absolutely nothing to do with the quality of the data

Quantitative: characteristics that can be expressed numerically. Any mathematical manipulation that is carried out on them will have meaning.e.g.: height, length, volume, number of DMFT’s

(variates)


FACTS ABOUT DATAFACTS ABOUT DATA

Data Set:

• Relates to a given group of data

• Generally denoted with brackets

e.g.: Q = {17, 15, 18, 13, 12}

Data Point:

• A single observation in a data set

e.g.: 15 is the second data point in the above data set

Data is Plural:

• Datum is singular


FACTS ABOUT DATAFACTS ABOUT DATA

Raw Data:• Data still in the form that it was when

originally gathered.

e.g.: A = {14, 11, 17, 9, 12}

Rank Ordering:• Rearranging data in order – usually ascending

e.g.: A = {9, 11, 12, 14, 17}


DATA MANAGEMENTDATA MANAGEMENT

Grouping data to make it easier to understand.

Descriptive Technique:• Used to describe and summarize a set of

numerical data• Tabular and graphical methods• Apply to generalizations made about the

group studied


DESCRIPTIVE DATA DISPLAY TYPESDESCRIPTIVE DATA DISPLAY TYPES

19 28 30 44 41 41

25 33 39 49 42 38

26 35 41 38 33 40

30 38 44 31 36 46

An Array:A group of scores arranged from lowest to highest in value.e.g.: Histology test results – 24 students:

= Raw Data

Array:19, 25, 26, 28, 30, 30, 31, 33, 33, 35, 36, 38, 38, 38, 39, 40, 41, 41, 41, 42, 44, 44, 46, 49 / 50 total



Arrays are bulky and hard to read, thus an alternative is:

Frequency Distribution:

• An organization of scores from lowest to highest which includes the number of times each score value occurs in the data set.



Frequency Distribution – 3 Types:1. Ungrouped• Each possible score value of the

variable being measured is represented in the display and the frequency of occurrence of the value is recorded. Sample:



Score F Score F Score F

50 40 1 30 2

49 1 39 1 29

48 38 3 28 1

47 37 27

46 1 36 1 26 1

45 35 1 25 1

Frequency Distribution – Ungrouped:



Scores Grouped Cumulative

16-20 1 1

21-25 1 2

26-30 4 6

31-35 3 9

36-40 6 15

41-45 7 22

46-50 2 24

2. Grouped Frequency Distribution:

When a broad range of values on the measurement is possible (i.e. > 30), the range is collapsed by grouping scores together into smaller value ranges.



Scores Grouped Cumulative

16-20 1 1

21-25 1 2

26-30 4 6

31-35 3 9

36-40 6 15

41-45 7 22

46-50 2 24

3. Cumulative Frequency Distribution:

Used with score groupings where the frequency of any one group includes all instances of scores in that group plus all the groups of lower score values.


GRAPHS AND TABLESGRAPHS AND TABLES

• Histograms

• Polygons – most frequently used

• Bar graphs

• Pie charts


PRINCIPLES FOR CONSTRUCTING PRINCIPLES FOR CONSTRUCTING GRAPHS AND TABLESGRAPHS AND TABLES

(Course supplement Pages 6, 7, 8)1. Items in separate columns should be clearly

defined and the units of measure of the observation included

2. A suitable descriptive title should define the contents as a whole

3. Rate statistics clearly stated (per 100 or per 1,000)

4. When possible and practical, frequency distribution should be in full


PRINCIPLES FOR CONSTRUCTING PRINCIPLES FOR CONSTRUCTING GRAPHS AND TABLESGRAPHS AND TABLES

5. When using rates or proportions, include numbers of observations

6. Clearly state when using percentage

7. Do not include too much on the same table

8. If observations are excluded, give reason and criteria


GRAPHING TECHNIQUESGRAPHING TECHNIQUES

• Descriptive data in pictorial fashion as a graph

Y Axis (Ordinate) = vertical axis• Represents frequency of occurrence• Represents score valueX Axis (Abscissa) = horizontal axis• Represents scale of measurement of the

characteristic of the sample• Indicates the variable or group studied


FREQUENCY HISTOGRAMFREQUENCY HISTOGRAM

See course supplement page 8.

• A histogram is a graphical method for variate (quantitative characteristic) data. Note that there is no space between the vertical bars.


FREQUENCY POLYGONFREQUENCY POLYGON


• A line graph created by joining the frequency / scale value coordinate points for each value in the scale represented. Used for variate data.


BAR GRAPHBAR GRAPH


2-dimensional pictorial display of attribute data that are discrete in nature

• Bars do not touch


CENTRAL TENDENCYCENTRAL TENDENCY

Term in statistics that describes where the data set is located.

Measures of Central TendencyUsed to describe what is typical in the sample

group based on the data gathered.Three Main Indicators:- Mean

- Median- Mode



Mean = arithmetic average of scores

• Mean symbol is ( x )

• Scores are all added then divided by the number of scores.

• The most common measure:

Data set {3, 7, 9, 4, 9, 16} = 48 / 6 = 8



Median:Is the point that divides the distribution of scores into 2

equal parts – 50 / 50• With odd set of numbers, median is the datum in the

middle:i.e.: {3, 7, 2, 5, 9} rearranged to {2, 3, 5, 7, 9}median = 5

• With even set of numbers, median is the average of the two middle values:i.e.: {4, 7, 1, 3, 8, 2} rearranged to {1, 2, 3, 4, 7, 8}

3 + 4 = 7 / 2 median = 3.5



Mode:

Is the most frequently occurring score in a distribution:

i.e.: {4, 3, 4, 9, 7, 2} mode = 4

i.e.: {3, 8, 4, 2, 4, 9, 7, 4, 9, 1, 9}

bimodal data set 4 and 9


QUESTIONSQUESTIONS

Determine the mode, mean and median for:1. Survival time, in months, for 10 patients

following a new cancer treatment:24, 8, 12, 3, 20, 18, 24, 19, 27, 25

2. Salaries of 7 dental hygienists and 2 dentists in a productive office:88,500 36,500 28,30080,000 34,000 28,30041,000 32,000 28,300


“If a statistician had her hair on fire and her feet in a block of ice, she would say that “on the average, she felt good.””

What is she referring to?

What is she ignoring?

algonquin college - janet ladas1 community dental health

Documents

proportion of people

new cases

people yeare

specific bits of data

simple number of cases

interpretation of numeric

science of data analysis

specific populationevaluating