Lesson 1. Introduction to Biostatistics and Epidemiology

Biostatistics and Epidemiology

Biostatistics and Epidemiology

Basic sciences of public health

Statistics

Branch of applied mathematics that deals with the collection, organization, presentation, analysis, and interpretation of data

Biostatistics

Application of statistics to problems in the biological sciences, health, and medicine

Epidemiology

Study of distribution and determinants of health, disease, injury in human populations

To control health problems

What does Epidemiology aims?

Address a public health question

1st Role of Quantitative Methods in Public Health

Generate a hypothesis

What does the 1st Role of Quantitative Methods in Public Health contain?

Hypothesis

An educated guess, scientific rationale, observations or anecdotal evidence (not scientifically tested), and results of prior studies

Conduct a study

2nd Role of Quantitative Methods in Public Health

Survey study, Surveillance study, Observational studies, Experimental studies

What does the 2nd Role of Quantitative Methods in Public Health contain?

Survey study

Asking and checking if individuals have a common profile

Survey study

Collecting information from a pool of respondents by asking multiple survey

Survey study

To estimate the extent of a disease in a population

Survey study

"Occular visit”

Surveillance study

For monitoring

Surveillance study

Used to monitor or detect a specific disease

Surveillance study

Collection of reliable and timely information about health conditions in the population to improve health

Observational studies

Cause-and-effect

Observational studies

Looking for the potential risk factor or cause of a disease

Observational studies

Investigates the association between exposure and a disease outcome and the exposed group from unexposed groups

Observational studies

Placebo effect

Experimental studies

A type study that has an expected result

Experimental studies

Intentionally allocating people

Experimental studies

Perform interventions and testing

Experimental studies

Usually randomized, meaning the subjects are grouped by chance

Experimental studies

Investigates the association between exposure often therapeutic treatment and disease outcome, more on clinical traits

Collect data

Numerical facts, measurements, or observations obtained from an investigation to answer a question

Collect data

3rd Role of Quantitative Methods in Public Health

Collect data

Influences of temporal and seasonal trends on the reliability and accuracy of data

Table, Graphs, Summary Measures

What are the Descriptive Statistical methods?

Describe the observation/data

4th Role of Quantitative Methods in Public Health

Descriptive statistical method

What does the 4th Role of Quantitative Methods in Public Health contain?

Assess the strength of evidence for/against a hypothesis; evaluate the data

5th Role of Quantitative Methods in Public Health

Recommend interventions or preventive programs

6th Role of Quantitative Methods in Public Health

Recommend interventions or preventive programs

Study results prove or disprove the hypothesis and sometimes fall unto gray area of being unsure

Assess the strength of evidence for/against a hypothesis; evaluate the data

Generalize conclusions from the data collected from the sample groups

Asses the strength of evidence for/against a hypothesis; evaluate the data

To ask further questions and suggest future research to strengthen research or widen options

Descriptive Statistics, Inferential Statistics

Types of Statistics

Descriptive Statistics

Deals with the collection and presentation of data and collection of summarizing values to describe it group characteristics

Descriptive Statistics

Interprets data like graphs

Inferential Statistics

Deals with predictions and inferences based on the analysis and interpretation of the results of the information gathered by the statistician

Inference

Conclusion reached on the basis of evidence and reasoning

Variables

Numerical characteristics or attributes associated with the population being studied

Qualitaive (Categorical), Quantitative

Types of Variables

Qualitative/Catergorical

Ex. civil status, socioeconomic status, blood type

Quantitative

Leaning onto values

Discrete, Continuous

Types of Quantitative

Discrete

Countable and finite

Discrete

Obtained by merely counting

Discrete

Ex. Population

Continuous

Measurable, uncountable, infinite

Continuous

Obtained by measuring

Continuous

Ex. Age and Height

Nominal, Ordinal, Interval, Ratio

Scales of Measurement

Nominal

Has no inherent order or hierarchy

Nominal

Ex. Sex, Gender, Nationality, Marital Status, Religion, Race, Hair color, Country

Ordinal

More subjective

Ordinal

Ordered, but differences between values are not important

Ordinal

Ex. Ratings, Mood Scale, Socioeconomic status, Educational Attainment

Interval

Ordered, constant scale, has no natural zero

Interval

Ex. Temperature, pH scale, credit score

Ratio

Ordered, constant scale, has natural zero

Ratio

Ex. Height, Weight, Mass, Length, Duration, Money, Age, Speed

Population

Group of people, animals, places, things, or ideas to which any conclusions based on characteristics of a sample will be applied

Sample

Subgroup, small part, or portion of the population

Slovin’s Formula

A formula to find the value of the sample (n)

Sample (n) is equal to population (N) divided by 1 plus population (N) times sampling error (e) squared

State the Slovin’s Formula

Probability sampling, Non-probability sampling

Types of Sampling Technique

Simple random sampling, Systematic/Quasi-random sampling, Stratified random sampling, Cluster sampling, Multi-stage sampling

Types of Probability Sampling

Simple Random Sampling

Lottery Method

Simple Random Sampling

Most commonly used probability sampling

Simple Random Sampling

Each member of the population has an equal chance of being selected

Simple Random Sampling

The researcher randomly selects a subset of participants from a population

Probability Sampling

Every element of the population has a chance to participate in the sample

Probability Sampling

Makes use of randomization, making it more time-consuming and costly

Systematic/Quasi-Random Sampling

Selects samples at a particular preset interval from a larger population according to a random starting point

Systematic/Quasi-Random Sampling

A frequently used method of sampling when a complete list of the population is available

Systematic/Quasi-Random Sampling

Ex. Selecting every 20th person in a line of 20 moviegoers

Stratified Random Sampling

Involves the division of a population into smaller subgroups called “strata”

Stratified Random Sampling

Groups a population by certain criteria or a shared attribute and then undergoes lottery method

Cluster Sampling

Researchers divide a population into clusters, such as districts or schools, and the randomly select some of these clusters as your sample

Cluster Sampling

Often used to study large populations, particularly those that are widely geographical dispersed

Cluster Sampling

If the population or geographical are is too big, it is divided into sub-parts

Multi-stage Sampling

Researchers divide the population into clusters and select some clusters at the first stage