ppt

COMMUNITY DENTAL HEALTH

Algonquin College - Janet Ladas

STATISTICSStatistics 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.


STATISTICSForeign 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 BIOSTATISTICSBiostatistics:The mathematics of collection, organization and interpretation of numeric data having to do with living organisms.

Techniques to manage data:DescriptiveInferential


INTRODUCTION TO BIOSTATISTICSUses for data: (To name a few)Designing a health care program or facilityEvaluating the effectiveness of an ongoing programDetermining needs of a specific populationEvaluating the accuracy of a journal article


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


METHODS OF MEASURING ORAL DISEASECounts:A simple number of cases of occurrenceUseful 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 prevalence

e.g. 12 cases in a population of 1,500 studentsDoes not include a time dimension thus includes new cases as well as longstanding ones


METHODS OF MEASURING ORAL DISEASERates: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 / yeare.g.: 12 / 1,500 / 2000


METHODS OF MEASURING ORAL DISEASEMortality Rate:The proportion of people who die from the disease during a period of time

formula: # of deaths / 100,000 people / yeare.g.: 8 / 1,500 / 2000Case Rate:Frequency of occurrence of the condition / disease

formula: # of occurrences / # of births / yeare.g.: 1 / 700 / 2001 (Cleft Palatte Cases)n.b. rates can be converted into percentages


INDEXES (INDICES)An index is a measure of quantification of epidemiological dataA numerical value on a graduated scaleScores correspond to specific criteriaHave definite upper and lower limits

Examples:DMFTs caries activity best known irreversibleRCI root caries - irreversible


INDEXES (INDICES)GBI Gingival Bleeding reversibleCPITN Community Periodontal Index of Treatment NeedsDFI Dental Fluorosis

Note:No generic, all purpose scaleDepends on the reason for using that measure, how to handle it reliably and what you want to demonstrate


DENTAL HEALTH INDICESDental conditions readily lend themselves to study because we have specific tools for speed and accuracy of measurement.Index PropertiesClear, simple, objectiveValid measures what it is supposed toReliable consistent on repetitionQuantifiable data can be analyzedSensitive can detect small shifts in either directionAcceptable not painful or demeaning to the subjectClinically significant and meaningful


CARIES ACTIVITIES INDICESDMFT : decayed, missing, filled permanent teethdeft : primary teethEach 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 cariesTeeth not deemed as missing = unerupted, congenitally absent, accidentally lost or extracted for ortho. PurposeThird 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 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 dataQuantitative: 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 DMFTs(variates)


FACTS ABOUT DATAData Set: Relates to a given group of dataGenerally 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 setData is Plural:Datum is singular


FACTS ABOUT DATARaw 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 MANAGEMENTGrouping data to make it easier to understand.Descriptive Technique:Used to describe and summarize a set of numerical dataTabular and graphical methodsApply to generalizations made about the group studied


DESCRIPTIVE DATA DISPLAY TYPESAn Array:A group of scores arranged from lowest to highest in value.e.g.: Histology test results 24 students:= Raw DataArray: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

192830444141253339494238263541383340303844313646


DESCRIPTIVE DATA DISPLAY TYPESArrays 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.


DESCRIPTIVE DATA DISPLAY TYPESFrequency Distribution 3 Types:UngroupedEach possible score value of the variable being measured is represented in the display and the frequency of occurrence of the value is recorded. Sample:


DESCRIPTIVE DATA DISPLAY TYPESFrequency Distribution Ungrouped:

ScoreFScoreFScoreF50401302491391294838328147372746136126145351251


DESCRIPTIVE DATA DISPLAY TYPES2. 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.

ScoresGroupedCumulative16-201121-251226-304631-353936-4061541-4572246-50224


DESCRIPTIVE DATA DISPLAY TYPES3. 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.

ScoresGroupedCumulative16-201121-251226-304631-353936-4061541-4572246-50224


GRAPHS AND TABLESHistogramsPolygons most frequently usedBar graphsPie charts


PRINCIPLES FOR CONSTRUCTING GRAPHS AND TABLES(Course supplement Pages 6, 7, 8)Items in separate columns should be clearly defined and the units of measure of the observation includedA suitable descriptive title should define the contents as a wholeRate statistics clearly stated (per 100 or per 1,000)When possible and practical, frequency distribution should be in full


PRINCIPLES FOR CONSTRUCTING GRAPHS AND TABLES5.When using rates or proportions, include numbers of observations6.Clearly state when using percentage7.Do not include too much on the same table8.If observations are excluded, give reason and criteria


GRAPHING TECHNIQUESDescriptive data in pictorial fashion as a graph

Y Axis (Ordinate) = vertical axisRepresents frequency of occurrenceRepresents score value

X Axis (Abscissa) = horizontal axisRepresents scale of measurement of the characteristic of the sampleIndicates the variable or group studied


FREQUENCY HISTOGRAMSee 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 POLYGONSee course supplement page 9.A line graph created by joining the frequency / scale value coordinate points for each value in the scale represented. Used for variate data.


BAR GRAPHSee course supplement page 10.2-dimensional pictorial display of attribute data that are discrete in natureBars do not touch


CENTRAL TENDENCYTerm 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


CENTRAL TENDENCYMean = arithmetic average of scoresMean 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


CENTRAL TENDENCYMedian:Is the point that divides the distribution of scores into 2 equal parts 50 / 50With 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 = 5With 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


CENTRAL TENDENCYMode:Is the most frequently occurring score in a distribution:i.e.: {4, 3, 4, 9, 7, 2} mode = 4i.e.: {3, 8, 4, 2, 4, 9, 7, 4, 9, 1, 9}bimodal data set 4 and 9


QUESTIONSDetermine the mode, mean and median for:Survival time, in months, for 10 patients following a new cancer treatment:24, 8, 12, 3, 20, 18, 24, 19, 27, 25Salaries of 7 dental hygienists and 2 dentists in a productive office:88,50036,50028,30080,00034,00028,30041,00032,00028,300


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?


ppt

Documents

Transcript of ppt