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BIOSTAT > PRELIM LEC 1 (1): INTRODUCTION TO BIOSTATISTICS > Flashcards

PRELIM LEC 1 (1): INTRODUCTION TO BIOSTATISTICS Flashcards

1
Q

INTRODUCTION TO BIOSTATISTICS

are the basic sciences of public health

A

Epidemiology and biostatistics

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2
Q

INTRODUCTION TO BIOSTATISTICS

is a branch of applied mathematics which deals with the collection, organization, presentation, analysis and interpretation of data.

A

Statistics

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3
Q

INTRODUCTION TO BIOSTATISTICS

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

A

Biostatistics

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4
Q

INTRODUCTION TO BIOSTATISTICS

is the study of the distribution and determinants of health, disease, or injury in human populations and the application of this study to the control of health problems

A

Epidemiology

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5
Q

ROLE OF QUANTITATIVE METHODS IN PUBLIC HEALTH

Generate a hypothesis
 Based on scientific rationale
 Based on observations or anecdotal evidence
(not scientifically tested)
 Based on results of prior studies
 Examples of a hypothesis
 The risk of developing lung cancer remains constant
 in the last five years
 The use of a cell phone is associated with developing
 brain tumor
Vioxx increases the risk of heart disease

A

Address a public health question

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6
Q

ROLE OF QUANTITATIVE METHODS IN PUBLIC HEALTH

 Survey study is used to estimate the extent of the disease in the population
 Surveillance study is designed to monitor or detect specific diseases
 Observational studies investigate association between an exposure and a disease outcome  They rely on “natural” allocation of individuals to exposed or non-exposed groups
 Experimental studies also investigate the association between an exposure, often therapeutic treatment, and disease outcome  Individuals are “intentionally” placed into the treatment groups by the investigators

A

Conduct a study

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7
Q

is used to estimate the extent of the disease in the population

A

Survey study

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8
Q

is designed to monitor or detect specific diseases

A

Surveillance study

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9
Q

investigate association between an exposure and a disease outcome  They rely on “natural” allocation of individuals to exposed or non-exposed groups

A

Observational studies

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10
Q

also investigate the association between an exposure, often therapeutic treatment, and disease outcome
 Individuals are “intentionally” placed into the treatment groups by the investigators

A

Experimental studies

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11
Q

ROLE OF QUANTITATIVE METHODS IN PUBLIC HEALTH

 Numerical facts, measurements, or observations obtained from an investigation to answer a question
 Influences of temporal and seasonal trends on the reliability and accuracy of data
 Examples:  The number of lung cancer cases from 1960–2000 in the United States
 The number of deaths from cardiovascular diseases in Whites and African Americans from 2000–2004

A

Collect data

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12
Q

ROLE OF QUANTITATIVE METHODS IN PUBLIC HEALTH

Descriptive statistical methods provide an exploratory assessment of the data from a study
 Exploratory data analysis techniques
 Organization and summarization of data
 Tables  Graphs  Summary measures

A

Describe the observation/data

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13
Q

methods provide an exploratory assessment of the data from a study

A

Descriptive statistical

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14
Q

ROLE OF QUANTITATIVE METHODS IN PUBLIC HEALTH

 Inferential statistical methods provide a confirmatory data analysis  Generalize conclusions from data from part of a group (sample) to the whole group (population)
 Assess the strength of the evidence  Make comparisons  Make predictions  Ask more questions; suggest future research

A

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

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15
Q

methods provide a confirmatory data analysis

A

Inferential statistical

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16
Q

ROLE OF QUANTITATIVE METHODS IN PUBLIC HEALTH

 The study results will prove or disprove the hypothesis, or sometimes fall into a grey area of “unsure”
 The study results appear in a peer-review publication and/or are disseminated to the public by other means
 Consequently, the policy or action can range from developing specific regulatory programs to general personal behavioral changes

A

Recommend interventions or preventive programs

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17
Q

2 TYPES OF STATISTICS

A

Descriptive statistics
Inferential statistics

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18
Q

deals with the collection and presentation of data and collection of summarizing values to describe its group characteristics

A

Descriptive statistics

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19
Q

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

A

Inferential statistics

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20
Q

numerical characteristics or attribute associated with the population being studied

A

Variables

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21
Q

2 TYPES OF VARIABLES

A

Categorical or Qualitative Variables
Numerical - Valued or Quantitative Variables

22
Q

example: Gender, Eye color, Blood Type, Civil Status, Socio Economic Status

A

Categorical or Qualitative Variables

23
Q

 Discrete - is a variable whose values are obtained by counting
 Continuous - is a variable whose values are obtained by measuring such as temperature, distance, area, age, height

A

Numerical - Valued or Quantitative Variables

24
Q

is a variable whose values are obtained by counting

A

Discrete

25
Q

is a variable whose values are obtained by measuring such as temperature, distance, area, age, height

A

Continuous

26
Q

4 SCALES OF MEASUREMENT

A

NOMINAL SCALE
ORDINAL SCALE
INTERVAL SCALE
RATIO SCALE

27
Q

Sex, Nationality

A

NOMINAL SCALE

28
Q

 ordered but differences between values are not important
 e.g., Likert scales, rank on a scale of 1..5 your degree of satisfaction
 e.g., pain ratings

A

ORDINAL SCALE

29
Q

 ordered, constant scale, but no natural zero
 e.g., temperature (C,F)

A

INTERVAL SCALE

30
Q

 ordered, constant scale, natural zero
 e.g., height, weight, age, length

A

RATIO SCALE

31
Q

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

A

Population

32
Q

subgroup of the population

A

Sample

33
Q

SLOVIN’S FORMULA:

A

n= N
_______
1+N(e)2

34
Q

SLOVIN’S FORMULA

where:
n – _______
N – population
1 – constant
e – sampling error

A

Sample

35
Q

SLOVIN’S FORMULA

where:
n – sample
N – _______
1 – constant
e – sampling error

A

Population

36
Q

SLOVIN’S FORMULA

where:
n – sample
N – population
1 – _______
e – sampling error

A

Constant

37
Q

SLOVIN’S FORMULA

where:
n – sample
N – population
1 – constant
e – ________

A

sampling error

38
Q

STAGES IN THE SELECTION OF A SAMPLE

A
  1. Define the target population
  2. Select a sampling frame
  3. Determine id a probability or nonprobability sampling method will be chosed
  4. Plan procedure for selecting sampling units
  5. Determine sample size
  6. Select actual sampling units
  7. Conduct fieldwork
39
Q

2 TYPES OF SAMPLING TECHNIQUES

A

PROBABILITY SAMPLING
NON-PROBABILITY SAMPLING

40
Q

the sample is a proportion (a certain percent) of the population and such sample is selected from the population by means of some systematic way in which every element of the population has a chance of being included in the sample
o Numerical - Valued or Quantitative Variables  Discrete - is a variable whose values are obtained by counting
 Continuous - is a variable whose values are obtained by measuring such as temperature, distance, area, age, height
SCALES OF MEASUREMENT
A. Nominal Scale  Sex, Nationality
B. Ordinal Scale  ordered but differences between values are not important
 e.g., Likert scales, rank on a scale of 1..5 your degree of satisfaction
 e.g., pain ratings
C. Interval Scale  ordered, constant scale, but no natural zero  e.g., temperature (C,F)
D. Ratio Scale  ordered, constant scale, natural zero  e.g., height, weight, age, length
SAMPLING TECHNIQUE
 Population o is defined as groups of people, animals, places, things or ideas to which any conclusions based on characteristics of a sample will be applied
 Sample o subgroup of the population
 SLOVIN’S FORMULA: n= _____N_____ 1 + N(e)2
where: n – sample N – population 1 – constant e – sampling error
STAGES IN THE SELECTION OF A SAMPLE
1. Define the target population 2. Select a sampling frame 3. Determine id a probability or nonprobability sampling method will be chosed
4. Plan procedure for selecting sampling units 5. Determine sample size 6. Select actual sampling units 7. Conduct fieldwork
 Types of Sampling Techniques
1. Probability Sampling  the sample is a proportion (a certain percent) of the population and such sample is selected from the population by
 Randomization is a feature of the selection process rather that an assumption about the structure of the population
 More complex, time consuming and more costly

A

Probability sampling

41
Q

The sample is not a proportion of the
population and there is no system in selecting the sample. The selection depends upon the situation.
 No assurance is given that each item has a chance of being included as a sample
 There is an assumption that there is an even distribution of characteristics within the population, believing that any sample would be representative

A

Non-probability sampling

42
Q

4 EXAMPLES OF PROBABILITY SAMPLING

A

Simple Random Samping
Stratified Random Sampling
Systematic Sampling
Cluster Sampling

43
Q

Lottery Method
This is the most popular and simplest method

A

Simple random Sampling

44
Q

the population is split into non - overlapping groups (“strata”), then simple random sampling is done on each group to form a sample

A

Stratified random sampling

45
Q

This method is widely employed because of its ease and convenience.
 A frequently used method of sampling when a complete list of the population is available It is also called Quasi - Random Sampling

A

Systematic Sampling

46
Q

When the geograpical area where the study is too big and the target population is too large

A

Cluster sampling

47
Q

2 EXAMPLES OF NON-PROBABILITY SAMPLING

A

Convenience sampling
Purposive sampling

48
Q


no system of selection but only those whom the researcher or interviewer meet by chance are include the sample.
 process of picking out people in the most convenient and fastest way to immediately get their reactions to a certain hot and controversial issue
 not representative of target population because sample are selected if they can be accessed easily and conveniently.
  
Advantage: easy to use Disadvantage: bias is present
it could deliver accurate resultwhen the population is homogeneous

A

Convenience sampling

49
Q

 the respondents are chosen based on their knowledge of the information desired.

A

Purposive sampling

50
Q

specified number of persons of certain types are include in the sample.

A

quota sampling

51
Q

sample is taken based on certain judgements about the overall population

A

Judgment sampling

BIOSTAT (4 decks)

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