M2 Flashcards by Josh Vincent Sario

2 Sources of Data Collection

Primary data and secondary data

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– 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

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– 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

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what are the methods of data collection

Direct/Interview method and Indirect/Questionnaire

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Types of Interview: requires an appointment w/ the respondents

formal

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Types of Interview: by chance interview

Informal

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Types of Interview: involves a patient & his health provides

Clinical

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Types of Interview: wider & deeper coverage as in investigative or detective cases

In-depth

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Types of Interview: solicits views and opinions from a group of people

focus

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Types of Interview: – interviewed person has given the task of providing pieces of advice.
i.e. – counseling given by guidance counselor

Non-Directed

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set of written & planned
questions related to a particular topic intended to answer
the problem of the study.

Indirect or Questionnaire

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– oral type of questionnaire w/ a face to face contact bet. the researcher and the respondents.

Direct or Interview method

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Types of Questionnaire: answerable through options or choices.

close ended

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Types of Questionnaire: questions that require further explanation in phrases or paragraphs.
i.e. narrative responses

Open ended

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Types of Questionnaire: data obtained through births, deaths,
marriages, licenses and census.

registration

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Types of Questionnaire: used by scientific researches

Experimental

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– 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

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2 General Types of Sampling Design

Non probability sample and probability sample

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a sampling procedure wherein the probability of each element being included in the sample is unknown

Non probability sample

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as a result there is no way of assessing the reliability of the sample results

Non probability sample

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any sampling procedure wherein each element in the population has a known probability of being included in the sample.

Probability sample

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4 types of Non-probability sampling

Judgment or Purposive sampling
Accidental or Haphazard sampling
Quota sampling
Snowball technique

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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

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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

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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

1. Simple random sampling 2. Systematic probability sampling 3. Stratified random sampling 3.1. stratified random sampling w/ equal allocation 3.2. Stratified random sampling with proportional allocation 4. 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

1. Narrative or Textual 2. Graphical 3. 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:

1. Mean 2. Median 3. 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

1. Ungrouped data or Raw or Scattered 2. 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

M2 Flashcards

(66 cards)