M2 Flashcards
2 Sources of Data Collection
Primary data and secondary data
– obtained first hand by the investigator from first hand sources.
i.e. – thesis & dissertations
- interview and questionnaire
- letters, diaries and autobiographies
- experimentation
- journals and newspapers
Primary data
– are finished products taken from raw materials.
- data w/c are already existing.
i.e. – data obtained from registry of cases of hospitals
- documented materials
- book of factual information i.e. textbooks
Secondary data
what are the methods of data collection
Direct/Interview method and Indirect/Questionnaire
Types of Interview: requires an appointment w/ the respondents
formal
Types of Interview: by chance interview
Informal
Types of Interview: involves a patient & his health provides
Clinical
Types of Interview: wider & deeper coverage as in investigative or detective cases
In-depth
Types of Interview: solicits views and opinions from a group of people
focus
Types of Interview: – interviewed person has given the task of providing pieces of advice.
i.e. – counseling given by guidance counselor
Non-Directed
set of written & planned
questions related to a particular topic intended to answer
the problem of the study.
Indirect or Questionnaire
– oral type of questionnaire w/ a face to face contact bet. the researcher and the respondents.
Direct or Interview method
Types of Questionnaire: answerable through options or choices.
close ended
Types of Questionnaire: questions that require further explanation in phrases or paragraphs.
i.e. narrative responses
Open ended
Types of Questionnaire: data obtained through births, deaths,
marriages, licenses and census.
registration
Types of Questionnaire: used by scientific researches
Experimental
– the act of studying only a portion of the population to represent the whole.
i.e. diagnosing a patient based on his blood count
Sampling
2 General Types of Sampling Design
Non probability sample and probability sample
a sampling procedure wherein the probability of each element being included in the sample is unknown
Non probability sample
- as a result there is no way of assessing the reliability of the sample results
Non probability sample
any sampling procedure wherein each element in the population has a known probability of being included in the sample.
Probability sample
4 types of Non-probability sampling
- Judgment or Purposive sampling
- Accidental or Haphazard sampling
- Quota sampling
- Snowball technique
a representative sample of the population is selected based on an expert’s subjective judgment or on some pre-specified criteria.
i.e. an area is selected bec. the community leaders are known to the investigators.
Judgment or Purposive sampling
if the researcher used in his study whatever items come at hand or whoever is available.
i.e. he may interview the first 50 people who enters a department store or he may ask for volunteers
Accidental or Haphazard sampling
collection of data continues until the pre-specified quota is met.
i.e. house to house interview
Quota sampling
used in confidential researches wherein the other respondents are picked out by the previous respondent.
- frequently used when studying “ hidden population” like drug users & prostitutes, w/ HIV positive individuals
Snowball technique
6 Types of Probability
- Simple random sampling
- Systematic probability sampling
- Stratified random sampling
3.1. stratified random sampling w/ equal allocation
3.2. Stratified random sampling with proportional allocation - Cluster
there is an equal chance for every member of the population of being included in the sample
Simple random sampling
Simple Random: draw lots
method.
i.e. rolling pieces of paper w/ the names of the population & have it selected by draw lots
fishbowl technique or lottery method
Simple Random: done when the population is large.
i.e. w/ eyes closed using a pencil pinpoint at any location a number in the table by chance.
table of random numbers
a technique for selecting members of a sample by picking out every Kth of the population
Systematic probability sampling
a pop. w/c is composed of several strata or subgroups.
Stratified random sampling
Type of strat random: samples per group or strata
i.e. – department store, location, industry type
stratified random sampling w/ equal allocation
Type of strat random: – samples per group depends on the pop. per group.
i.e. – the bigger the pop., the more the samples; the smaller the pop., the smaller the sample.
Stratified random sampling with proportional allocation
– pop. w/c is divided into separate group of elements called clusters.
i.e. – area sampling such as 5 city blocks, clusters or groups of students.
Cluster
n = [N/(1 + N(e)^2)]
Sloven’s formula
3 Methods of Data Presentation
- Narrative or Textual
- Graphical
- Tabular
Method of data pres.: paragraph form
Narrative or Textual
Method of data pres.: – in graph
i.e. bar graph, histogram, pie graph, line diagram
Graphical
Method of data pres.: data w/c include lots of figures & makes use of a statistical table.
Tabular
3 Measures of Central Tendency:
- Mean
- Median
- Mode
the sum of all the cases divided by the number cases.
Mean
the middle most score in a distribution.
Median
the midpoint of the interval containing the largest number of cases.
Mode
2 Ways of Measuring Central Tendency
- Ungrouped data or Raw or Scattered
- Grouped data
Way of Measuring Central Tendency: – the exact values of the observations are retained
Ungrouped data or Raw or Scattered
Way of Measuring Central Tendency: – they are cast in a frequency distribution
Grouped data
(N + 1) / 2
Median
– frequently occuring # in the series
- score with greatest frequency
- determined through careful Inspection
Mode
tabular arrangement of data into classes or categories together w/ their corresponding class frequency.
Frequency distribution table
HS – LS
Range
In a hospital, every 5th patient entering the emergency room is selected for a study. What sampling technique is being used?
systematic sampling
Which of the following is a disadvantage of convenience sampling?
- It may lead to biased results.
- It requires specialized equipment
- It is suitable for large populations.
- It is time-consuming.
- It may lead to biased results.
Which of the following is an example of quantitative data?
- Height
- Blood type
- Gender
- Eye color
Height
In which type of sampling, the population is divided into subgroups, and then samples are randomly selected from each subgroup?
Stratified sampling
What is the primary goal of random sampling?
- To ensure that the sample size is large enough.
- To eliminate outliers from the dataset.
- To reduce bias and increase representativeness.
- To minimize the need for statistical analysis.
To reduce bias and increase representativeness.
What is a representative sample?
- A sample that includes only outliers.
- A sample with the highest variability.
- A sample that reflects the characteristics of the population.
- A sample with the smallest possible size.
A sample that reflects the characteristics of the population.
A researcher wants to study the dietary habits of adolescents from various socioeconomic backgrounds. What sampling technique would be appropriate?
Stratified sampling
Which of the following is an example of non-probability sampling?
- Simple random sampling
- Stratified sampling
- Convenience sampling
- Systematic sampling
Convenience sampling
A researcher selects several hospitals and then samples patients within each selected hospital. What sampling technique is being used?
- Stratified sampling
- Simple random sampling
- Cluster sampling
- Convenience sampling
Cluster sampling
In which type of sampling technique does every member of the population have an equal chance of being selected?
Simple random sampling
What is the first step in the process of data collection?
designing the study
What is the purpose of stratified sampling?
Correct answer:
- To ensure representation of different subgroups.
- To select every nth individual from a list.
- To divide the population into convenient groups.
- To select individuals based on their willingness to participate
To ensure representation of different subgroups.
What is a population in the context of biostatistics?
- The entire group under study.
- An outlier in a dataset.
- A small subset of a larger group.
- A sample from a different study.
The entire group under study.
What is the purpose of data collection in biostatistics?
- To analyze existing datasets.
- To present results graphically.
- To create complex statistical models.
- To draw conclusions and make inferences about a population
To draw conclusions and make inferences about a population
A researcher selects a random city and then samples households within that city. What sampling technique is being used?
cluster sampling
