INTRODUCTION AND DEFINITIONS STATISTICS INTRODUCTION AND DEFINITIONS

STATISTICS A field of study concerned with methods and procedures of: Collection, Organization, Classification & Summarization of data. (Descriptive Statistics) Analysis, and Drawing of inferences about a body of data when only a part of data are observed. ( Analytic Statistics)

BIOSTATISTICS When the data being analyzed are derived from biological and medical sciences, the term “ Biostatistics” is used.

ADVANTAGES 1. Carrying out a research Statistical analysis should be considered in the planning phase of the study 2. Evaluating published articles Statistical errors are common in clinical researches that may invalidate the conclusion.

ADVANTAGES 3. Ethical consideration It is unethical to use erroneous statistics especially in scientific publications. Using harmful or ineffective treatment or avoidance of useful treatment can occur if the statistics is wrong. 4. Professional and personal satisfaction

PURPOSES 3. Sampling and generalization 1. Data reduction By condensing data to manageable proportions thus facilitating interpretation 2. Evaluate role of chance To see if the effect of a certain event is a real one 3. Sampling and generalization What proportion of discharged patients required readmission? What are their characteristics? The answer required generalization of the sample's result.

APPLICATIONS Are the differences between groups significant? Are these two measures related or associated? Can one predict the value of one variable from knowledge of the values of other variables؟

Variables A characteristic that takes on different values things.eg.

Quantitative Variables Qualitative Variables The variable that can be measured in the usual sense of measurement as age , weight, height,… It is the variable that can not be measured in the usual sense but can be described or categorized ..Socio-economic

QUALITATIVE VARIABLE . eg.; - socio-economic groups. ill person with medical diagnosis In this case we count the number of individuals falling into each category as the socioeconomic status, diagnostic category,…

It is characterized by gaps or interruptions Quantitative Variables DISCRETE VARIABLE It is characterized by gaps or interruptions CONTINOUS VARIABLE It does not posses the gaps or interruption, It can assume any value within a in the values specified interval of values that it can assume. assumed by any variable - The number of daily admissions -Weight, -The number of decayed, missing or filled teeth -Height, -Mid-arm circumference per child

VARIABLES SCALE 1. NOMINAL SCALE It uses names, numbers or other symbols. Each measurement assigned to a limited number of unordered categories and fall in only one category. eg. males & females 2. ORDINAL SCALE to assigned Each measurement a limited number of categories that are ranked in a graded order. ( 1st, 2nd, 3rd..) .

VARIABLES SCALE 3. INTERVAL SCALE Each measurement is assigned to one of unlimited categories that are equally spaced with NO true zero point. 4. RATIO SCALE Measurement begins at a true zero point and the scale has equal intervals

POPULATION POPULATION OF ENTITIES Largest collection of entities that had common characteristics for which we have an interest at a particular time. POPULATION OF VARIABLES It is the largest collection of values of a random variable for which we have an interest at a particular time.

SAMPLE Sample of entities: Sample of variables: It is part or subset of the population Sample of entities: which is a subset of population of entities Sample of variables: which is subset of population of variables

GROUPED DATA To group a set of observations, we select a set of contiguous, non overlapping intervals, such that each value in the set of observation can be placed in one, and only one, of the interval, and no single observation should be missed. The interval is called: CLASS INTEVAL.

NUMBER OF CLASS INTERVALS The number of class intervals : Should not be too few because of the loss of important information. and Not too many because of the loss of the needed summarization . When there is a priori classification of that particular observation we can follow that classification ( annual tabulations), but when there is no such classification we can follow the Sturge's Rule

NUMBER OF CLASS INTERVALS Sturge's Rule: k=1+3.322 log n k= number of class intervals n= number of observations in the set The result should not be regarded as final, modification is possible

WIDTH OF CLASS INTERVAL The width of the class intervals should be the same, if possible. R W = -------- K W= Width of the class interval R= Range (largest value – smallest value) K= Number of class intervals

FREQUENCY DISTRIBUTION It determines the number of observations falling into each class interval Fasting blood glucoselevels < 60 60-62 63-65 Frequency 10 23 33 66-68 22 69-71 34 72+ 33 155

Fasting blood glucoselevels RELATIVE FREQUENCY DISTRIBUTION It determines the Fasting blood glucoselevels < 60 Frequency Relative frequency % 6.45 14.84 proportion of observation in the particular class interval relative to 10 23 60-62 63-65 33 21.29 the 66-68 22 14.19 total observations in the set. 69-71 34 21.94 72+ 33 21.29 155 100

CUMULATIVE FREQUENCY DISTRIBUTION < 60 60-62 Fasting blood glucose levels < 60 60-62 Frequency Cumulative frequency distribution 10 33 This is calculated by adding the number of observation in each class interval to the number of 10 23 63-65 33 66 observations in the 66-68 22 88 class interval above, starting from the 69-71 34 122 second class interval 72+ 33 155 onward. 155

EXERCI E S The followings 76 86 70 85 66 are the weights 55 73 49 79 56 (Kg) of 45 adult 62 65 77 78 71 male individuals attending a 69 72 47 primary health 88 58 68 59 care centers: 90 99 64 41 63 54 52 48 83 80 S

1 76 10 86 19 70 28 85 37 66 2 55 11 73 20 49 29 79 38 56 3 62 12 65 21 77 30 78 39 71 4 13 69 22 72 31 40 47 5 88 14 58 23 68 32 59 41 6 90 15 99 24 33 64 42 7 16 63 25 54 34 43 8 52 17 26 48 35 44 9 18 27 83 36 80 45

EXERCISE Construct a table showing: Frequency Relative frequency Cumulative frequency Cumulative relative frequency distribution.

Number of class intervals: K=1+3.322 log n =1+3.322 log45 =1+3.322 X 1.653 =6.4 =6 Width of class interval: R 99-41 W= ------ = ------- = 9.7 = 10 K 6

CLASS INTERVAL (Kg) 40-49 FREQUENCY 4 RELATIVE FREQUENCY % 8.9 CUMULATIVE FREQUENCY CUM.REL. FREQUENCY 50-59 7 15.6 11 24.5 60-69 24.4 22 48.9 70-79 13 28.9 35 77.8 80-89 42 93.4 90-99 3 6.7 45 100.1 Total

Thanks