Chapter 1 biostat

Larson & Farber, Elementary Statistics: Picturing the World, 3e 1

الرحيم الرحمن الله بسم


BiostatisticsBiostatisticscourse hand outcourse hand out


Course content• Chapter one introduces you to the study of

statistics generally. You are given the definition and led to how Biostatistics as an entity is derived.

• The main types of statistics are discussed as well as common terms encountered in the course of studying the subject, such as variables and their types, population, samples etc.

• Also this chapter introduces scales of measurement of numerical data which will help you to understand how data could be classified for easy and meaningful presentations. Scales as nominal, ordinal, interval and ratio are introduced in this unit.


• In the second chapter, we will learn the basic step in organizing the data. You will learn about the need to arrange data according to their magnitude in ascending or descending order as the case may be.(i.e. from the lowest to the highest or vice versa).

• You will also learn about frequency distribution to help you understand how frequent certain variables occur in a given series.

• This chapter also introduces the concept of range and practical application of Biostatistics to health care delivery.


• In the third chapter, we will look at the measure of central tendency, the single value that attempts to describe a set of data by identifying the central position within that set of data. Measures of central tendency are sometimes called measures of central location. They are also classed as summary statistics.

• In this chapter we will take three most common measures of central tendency. The mean (often called the average) is most likely the measure of central tendency that you are most familiar with, but there are others, such as the median and the mode.

•


• The mean, median and mode are all valid measures of central tendency, but under different conditions, some measures of central tendency become more appropriate to use than others.

• Therefore we will look at the mean, mode and median, and learn how to calculate them and under what conditions they are most appropriate to be used


• In chapter four, we will look measures of variation or dispersion. In the previous chapters we will take a look for several measures which are used to describe the central tendency of a distribution were considered. While the mean, median, etc. give useful information about the center of the data, We also need to know how “spread out” the numbers are about the center.

• The reason of measuring this scatter or dispersion is to obtain a single summary figure which adequately exhibits whether the distribution is compact or spread out.


• Hence it is essential to know how far these observations are scattered from each other or from the mean. Like different measures of central tendency, we will also loo the different measures of variation.

• Some of the commonly used measures of dispersion (variation) that we will learn are: Range, interquartile range, variance, standard deviation and coefficient of variation.

Chapter oneIntroduction to

Statistics


Introduction

• Most people familiar with statistics through radio, televisions, and newspapers and magazines.

• The following statements are statements that we hear every day

• A vitamins and mineral pill boosted certain immune response in older people by 64%.

• 95% of Somaliland community are un employed• Every five children born in sub-Saharan countries

two of them was dead for their first months.• 90% of Somali mother deliver their babies in the

homes


• Statistics is used in all fields of human endeavour.

• In sport: for example, a statistician may keep records of the number yards a running back and front during football game (3450 km)

• In public health: the number of human been dead due to cancer for the last decade.

• In education: the researcher might want to know if new methods of teaching are better than old ones.

• These are only a few examples of how statistics can be used in various occupations.


definition of statistics

Statistics is a field of study concerned with1- collection, organization, summarization and

analysis of data. 2- drawing of inferences about a body of data when

only a part of the data is observed. 3-interpret and communicate the results to others.


Biostatistics

• The tools of statistics are employed in many fields: business, education, psychology, agriculture, economics, … etc.

• Therefore, When the data analyzed are derived from the biological science and medicine we call biostatistics , to distinguish this particular application of statistical tools and concepts from any other tools.


Data and Statistics

Data consists of information coming from observations, counts, measurements, or responses.

Statistics is the science of collecting, organizing, analyzing, and interpreting data in order to make decisions.

A population is the collection of all outcomes, responses, measurement, or counts that are of interest.

A sample is a subset of a population.


Populations & SamplesExample:In a recent survey, 250 college students at Union College were asked if they smoked cigarettes regularly. 35 of the students said yes. Identify the population and the sample.

Responses of all students at Union College (population)

Responses of students in survey (sample)


Parameters & Statistics

A parameter is a numerical description of a population characteristic.

A statistic is a numerical description of a sample characteristic.

Parameter Population

Statistic Sample


Branches of Statistics

The study of statistics has two major branches: descriptive statistics and inferential statistics.

Statistics

Descriptive statistics

Inferential statistics

Involves the organization, summarization, and display of data.

Involves using a sample to draw conclusions about a population.

Data Classification


Data

• The raw material of Statistics is data. • Data are the values that the variable can

assume, data can be as figures. Figures result from the process of counting or from taking a measurement.

• For example: • When a hospital administrator counts the

number of patients (counting).• When a nurse weighs a patient

(measurement)


• We search for suitable data to serve as the raw material for our investigation.

• Such data are available from one or more of the following sources:

Internal sources (Routinely kept records. • For example:• - Hospital medical records contain immense

amounts of information on patients.- Hospital accounting records contain a wealth of

data on the facility’s Hospital activities.

Sources of Data


2- External sources.

The data we need may already exist in the form of published reports, commercially available data banks, or the research literature.

i.e. someone else has already asked the same question.


Surveys:• The source may be a survey, if the data needed is

about answering certain questions.

For example:

• If the administrator of a clinic wishes to obtain information regarding the mode of transportation used by patients to visit the clinic, then a survey may be conducted among patients to obtain this information.


• Experiments.• Frequently the data needed to answer a question

are available only as the result of an experiment.

• For example:• If a nurse wishes to know which of several

strategies is best for maximizing patient compliance, she might conduct an experiment in which the different strategies of motivating compliance are tried with different patients.


Types of Data

Data sets can consist of two types of data: qualitative data and quantitative data.

Data

Qualitative Data

Quantitative Data

Consists of attributes, labels, or

nonnumerical entries.

Consists of numerical

measurements or counts.


Qualitative and Quantitative Data

Example:The grade point averages of five students are listed in the table. Which data are qualitative data and which are quantitative data?

Student

GPA

Sally 3.22

Bob 3.98

Cindy 2.75

Mark 2.24

Kathy 3.84 Quantitative data

Qualitative data


Levels of Measurement

The level of measurement determines which statistical calculations are meaningful. The four levels of measurement are: nominal, ordinal, interval, and ratio.

Levels of

Measurement

Nominal

Ordinal

Interval

Ratio

Lowest to

highest


Nominal Level of Measurement

Data at the nominal level of measurement are qualitative only.

Levels of

Measurement

Nominal

Calculated using names, labels, or qualities. No mathematical computations can be made at this level.Colors

in the US flag

Names of students in your class

Textbooks you are

using this semester


Ordinal Level of Measurement

Data at the ordinal level of measurement are qualitative or quantitative.

Levels of

Measurement Arranged in order, but differences between data entries are not meaningful.

Class standings: freshman,

sophomore, junior, senior

Numbers on the back of

each player’s shirt

Ordinal

Top 50 songs

played on the radio


Interval Level of Measurement

Data at the interval level of measurement are quantitative. A zero entry simply represents a position on a scale; the entry is not an inherent zero.Levels

of Measurement

Arranged in order, the differences between data entries can be calculated.

Temperatures

Years on a timeline

Interval

Atlanta Braves World Series

victories


Ratio Level of Measurement

Data at the ratio level of measurement are similar to the interval level, but a zero entry is meaningful.

Levels of

Measurement

A ratio of two data values can be formed so one data value can be expressed as a ratio.

Ages Grade point averages

Ratio

Weights


Summary of Levels of Measurement

NoNoNoYesNominal

NoNoYesYesOrdinal

NoYesYesYesInterval

YesYesYesYesRatio

Determine if one data value is a

multiple of another

Subtract data

values

Arrange

data in

order

Put data in categor

ies

Level of measurem

ent


Methods of Data Collection

In an observational study, a researcher observes and measures characteristics of interest of part of a population.In an experiment, a treatment is applied to part of a population, and responses are observed.A simulation is the use of a mathematical or physical model to reproduce the conditions of a situation or process.A survey is an investigation of one or more characteristics of a population.

A census is a measurement of an entire population.A sampling is a measurement of part of a population.


Sampling techniques

A stratified sample has members from each segment of a population. This ensures that each segment from the population is represented.

Freshmen

Sophomores

Juniors Seniors


A cluster sample has all members from randomly selected segments of a population. This is used when the population falls into naturally occurring subgroups.

The city of Clarksville divided into city blocks.

All members in each selected group are used.


A systematic sample is a sample in which each member of the population is assigned a number. A starting number is randomly selected and sample members are selected at regular intervals.

Every fourth member is chosen.


A convenience sample consists only of available members of the population.

Example:You are doing a study to determine the number of years of education each teacher at your college has. Identify the sampling technique used if you select the samples listed.1.) You randomly select two different departments

and survey each teacher in those departments.

2.) You select only the teachers you currently have this semester.

3.) You divide the teachers up according to their department and then choose and survey some teachers in each department.

Continued.


Identifying the Sampling Technique

Example continued:You are doing a study to determine the number of years of education each teacher at your college has. Identify the sampling technique used if you select the samples listed.1.) This is a cluster sample because each

department is a naturally occurring subdivision.

2.) This is a convenience sample because you are using the teachers that are readily available to you.

3.) This is a stratified sample because the teachers are divided by department and some from each department are randomly selected.

Health & Medicine

Chapter 1 biostat