Introduction ( script # 1 )

8/3/2019 Introduction ( script # 1 )

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BIOSTATISTICS

These are some notes that the doctor mentioned before start:

- We have two exam the first exam will be on 5th of March, thesecond exam in 11

thof April, the doctor will put the course

description on e-Learning.

- The book of this course is biostatistics foundation foranalysis, and is available in book store.

- The doctor said if you listen to lecture the question of examwill be from the lecture.

- The doctor said if you come late for any reason it will bebetter don't enter the lecture because he dont like interruption .

So let's start the first lecture.

Definition

We start with statistics and biostatistics

Statistics: is a field of study concerned with:

- The collection, organization, summarization, and analysis ofdata.- The drawing inferences about a body of data when a part ofdata is observed.

So statistics in general it is about collecting data forExample collecting data from this class (how many males and

how many females, how many have Jordanian secondarycertificate or non Jordanian, your grade in secondary certificate,

your blood group.etc), this is what we called data

collection.


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Then inorganization we start organize the data for example,we divide blood grouping in four categories then we startanalysis the data to see what is the percentage of those with

blood group A or B..etc .

Then based on that we could drawinference says most ofstudent in this class lets say are males or most are females, or

most of student graduated from secondary schoolcertificate..etc.

The only difference between statistics in general and

biostatistics is in biostatistics we concerned with data from

biological sciences, we dont talk about wind speed ordirectionetc, we are concerned with data from biological

system, so biostatistics is tool of statistics used in biological

sciences.

Source of data

Where we get our data from?

If we want data about student in Jordan University of Scienceand technology, where we can get it? Usually if we want data

about student we go to student registration office or annual

report of university, and if we want data about healthy status ofJordanian we can collect it from annual report of ministry of

health ormedicalrecord.

If we dont have these annual records, we do a surveyby askingquestion to students and this is what we called surveys, or we

can do experiments for example take blood sample from

students and classify it to blood group, or we might go toscientific literature .

So we have four main sources for data:- Record- Surveys- Experiments- External source (we have people doing research or scientificliterature and we collecting data from these source)


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Common term used in statistics

-Population:the whole group we are interested in, for

example we interested in Jordan University of Science andTechnology students, so the whole number of university studentis called population

- Sample: is part of population, I take sample from student,so usually sample is less than population.

- Variables: some thing we want to study for example theweight or height of student, pulse rate, blood pressure, each onehas its own record and this what we called variable (varies from

one person to another ).

-Measurements: we do measurement and the measurementdivide in two parts for example if we want to take bloodpressure we bring some nurses to measure blood pressure, and

with measurement we have continuous number lets say the

weight of person 80.5 KG, with counting we dont havecontinuous number.

- Statistical inference:the conclusion we would drawbased on measurement or counting.

- Simple random sample: we have different type of sampleand we have one lecture talk about these type but the mostcommon one is the simple random sample for example if I wantto take sample contain 20 student just I can do that by pick the

names from the list and this what we mean by simple, randommeans every body in the class has the same chance of being

selected in the sample as any other person.


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Population

- Population of values is the largest collection of

values of a random variable, we call random variable

because lets say if I want to see the weight of students, each one

of you has different weight from other maybe 80 and if we havegood scale it will be 80.233, so each one has its own weight and

this is what we called random variable.

- finite population consist from fixed number, wehave in this class a finite population , I have a list of students forthis class lets say 230 of students its finite and not open , maybe the attendance is open but the number of students register in

M391 is finite population.

- Infinite population is endless succession ofpopulation, its infinite we dont know the number.

Sample

- Sample is part of population

-there are different types of sample as we mentioned (simple

random sample, clustered sample, stratified sample,systemically sample.etc), and each type of sample has its

specific techniques.

Variables- A variable is a characteristic that take different values as we

said height, weight and rate, different value for

- Diastolic blood pressure and heart rate, these are different

variable and each one has its own value.


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Type of variables

What are the types of variable?

- Quantitative variables: we could give specific value forit, we measure blood pressure, weight and height and this is

what we called quantitative variable from quantity, and whenwe say quantity we could have specific value for it either by

measuring or counting.

-Qualitative value: its quality and this mean lets say sickor not sick, diabetics (yes or no), so its describe quality of the

person or describe attitude of person .

- Random variables: we have two types of randomvariables:

1- Discrete random variables: we mean by discrete likewhen we say the number of males and females in this class 62 ,

we can't say 62.5 it's 62, I can't say the number of students withgroup O is 85,7 , and this is what we mean by discrete variables(fixed).

2- Continuous random variables:continuous mean

open, we can say the weight of one person 60.7 kg, usually in

continuous it's go with measurement (some thing we knowvariables after measurement like pulse rate) and remember with

discrete when we talk about the mean of discrete variable youcould get fraction, so the mean might be continuous

Measurement

Now how we could measure variables?We have four different scales in measurement:

1- Nominal scales: like males or females, blood group ( A,

B, AB,O)and this nominal scales it's mutually exclusive that'smean if a person in this category, he/she can't be in other


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category, the person can't be in A and B category ,and alsocan't be male and female, so either he/she will categories in this

group or other and this what we mean by mutually exclusive,and in nominal scale we can't say this group is better from

another group.

2- Ordinal scale: its measurement or observation of ranking

(sick, very sick, extremely sick), (poor, middle class, rich), so

it's scale and each one special category but carries with it rank.

3- Interval scale: its a distance between measurements, we

use interval scale with respect to weight, age (we see age from(0-5) years and from (5-18) yearsetc) and also we use it in

grading system for example we say A from (90-100) and B

from (80-90), so we have two measurements and value thatlocated between two measurement is called interval scale.

4- ratio scales: height, weight, length and there is true zeropoint and when we say ratio scale it's different from nominal

scale, let's say ratio of males to females, the ratio of those whogot A to those who got B ( the doctor said he will discuss it

later).

Statistical inference

It's a conclusion we draw based on data about population based

on information, usually we make the inference about populationbased on data we have from sample, let's say if we want to

measure the weight of the students, I take sample and found theaverage weight is 65 KG, then we could said based on data thatget from sample the average weight of JUST students is 65 KG,

so we make inference from the data that got from sample and

passed it to population and this is benefit of sample .In order to have good valid inference the sample should be

random sample (each one has the same chance of being selected

in sample).


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Simple random sample

If a sample of size n is drawn from a population of size N inway that every possible sample of size n has the same chance of

being selected and this is called simple random sample and it'smean every person in population has the same chance of being

selected.

If somebody want to take simple random from Irbid population,can we use telephone book to take simple random sample? It'swrong because not everybody in Irbid register in telephone

book, so not everybody has the same chance.

Data

Data is number result from measuring or counting as we said

discrete or continuous, so data is either measurement (bodyweight, body temperature) or counting (number of patient

admitted in king Abdullah hospital) and both measurement andcounting are called data and are also called variable because wehave different number of people admitted in hospital and also

we have different body temperature or body weight.

StatisticStatistic is very useful and the person who writes statisticalvalue, he/she could use it for passing judgment or sending

message.

for example in a class of two student, if someone says if I ranka second in a class my father will punch me and he/she can also

says I rank the last in a class, both statements are right but one

give different message from the other.

Statistic gives the right answer in (95%) of time if it properlyused, but if we take wrong sample the inference that we take

from the sample is wrong, for example if you stand inbasketball area and take sample to measure the height, you can'tmake inference for other students, or if we go to sick people to

measure pulse rate we can't make inference for otherpopulation.


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Why do we use statistic?

Usually we need statistic to make conclusion or take decision,for example you in a dental school when you graduate and hasyour own business, you would make statistical studies about

your patient (most of your patient are a adult, most of yourpatient are children, most of your patient complaining from

decaying teeth, most of your patient come in Sunday....etc),so we make inference about study.

Example

- Which drugs should be allowed on the market?

In a drug practice we make experiment about drug use, is itaffected or not?

-What Public Health programs should be pursued?Public programs like faxination, is it affected in minimizingspread of specific disease, another public program is screeningprogram to identify those who are diabetics from those who are

not , these are public program and we use them to identifydisease among population , so we apply our health service to a

specific group .

-What programs would reduce infant mortality?We make study and see the different in infant mortality ratebetween educated mothers and non educated.

- Are cell phones a good idea for drivers?

It's not good to use phone during driving, but in order to bescientific we have to make study and see the number of accidentresulting from using cell phones while driving compare to

number of accident without using it.


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Probability and Statistics

- Probability generalizes the concept of replicability Probability is magnified percent, so it means if we take 100, it

is properly magnified of those 100 who do this or that , forexample from the doctor experience he saw the probability of

passing in M391 is 96% or 98%.Based on that we could take decision, as student you take a

decision to take M391 or not, you need to pass this course.

-What is likely to happen in that specific situationLikely it is goes with probability; the higher the likely is the

higher probability is.

What is the likelihood of reaching the university if you come by

car and driving let's say 120 KM/h? The likely is lower thandriving at a speed of 118 KM/h.

Done by: Manar Malkawi

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Introduction ( script # 1 )