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2C PRELIMS > BIOSTATS > Flashcards

BIOSTATS Flashcards

1
Q

Study of distribution and determinants of health-related events in specified population for
prevention and control

A

EPIDEMIOLOGY

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2
Q

Percentage of population that has disease during given
time period

A

Prevalence

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3
Q

Percentage of population that contracts a disease in a
given time period or number of new people who gets
the disease

A

Incidence

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4
Q
  • More exploratory
  • Profiles characteristics
    of groups
  • Focuses on “what”
  • Assumes no
    hypothesis
  • Does not require
    comparisons between
    groups over time
A

DESCRIPTIVE

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5
Q

Explains
- More explanatory
- Analyzes why groups
has characteristics
- WHY
- Assumes a hypothesis
- Require comparison
bet groups over time

A

ANALYTICAL

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6
Q

Diseases (or any health-related events) don’t occur at
random
- Diseases (or other health events) have causal and
preventive factors which can be identified through
systematic investigation of population
- Epidemiology focuses on populations rather than
individual persons, tissues, or organ

A

Epidemiological Principles

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7
Q

science, which deals with collection, presentation,
analysis, and interpretation of numerical data

A

Statistics

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8
Q

study of probability distributions, sampling
distributions, estimation, hypothesis testing, variance
analysis, regression, and correlation analysis in
healthcare settings

A

BIOSTATISTICS

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9
Q

Collection, organization, summarization, and
presentation of data

A

Descriptive Stats

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10
Q
  • Generalizing from samples to population, performing
    estimations and hypothesis tests, determining
    relationships among variables and making predictions
  • Uses probability
A

Inferential Stats

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11
Q

Collection of all subjects of interest

A

Population

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12
Q

Units on which characteristics are measured

A

Subjects

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13
Q

Subset of population of interest

A

Sample

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14
Q

Characteristics which are being measured
and/or recorded.

A

Variables

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15
Q

Representations or each subject characteristic

A

Data Elements

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16
Q

A Collection of Data

A

Data Set

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17
Q

substance with no medical benefits or harm

A

Placebo

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18
Q

decision-making process for evaluating
claims about a population, based on information obtained
from samples.

A

Hypothesis Testing

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19
Q

categorizes data into distinct, non-overlapping groups
without any inherent order or ranking
- gender, hair color, type of pet, marital status, blood
type
- nationality, blood group, type of vaccines

A

NOMINAL

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20
Q

organizes data into categories that are rank able, yet it
does not establish exact differences between these
ranks
- education level, movie ratings, military ranks,
satisfaction levels
- pain level, Likert scale, hotel star ratings

A

ORDINAL

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21
Q

ranks data, and precise differences between units of
measure do exist; however, there is no meaningful zero
- temperature, IQ and SAT scores, calendar years
- time of day on 12 hours clock, pH levels, score on
depression scale
- heart rate, blood pressure, respiratory rate

A

INTERVAL

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22
Q

possesses all the characteristics of interval
measurement, and there exists a true zero. In addition,
true ratios exist when the same variable is measured
on two different members of the population
- height, weight, age, income
- blood glucose level, dosage of medication, oxygen
saturation levels, time on ventilator

A

RATIO

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23
Q

branch of mathematics working with data collection,
organization, analysis, interpretation and presentation
(Muhrey, 2008)

A

Statistics

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24
Q

science of conducting studies to collect, organize,
summarize, analyze, and draw conclusions from data
(Bluman, 2012)

A

Statistics

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25
Q

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

A

Biostatistics

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26
Q

characteristic or attribute that can assume a different
value; e.g. Gender, Intelligence Quotient

A

Variable

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27
Q

values that a variable can assume

A

Data

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28
Q

complete enumeration of population, best
source of data on population size and distribution
according to age

A

Census

29
Q

evaluating health status of a
population

A

Prevalence Survey

30
Q

Identify risk factors

A

Risk Factor Investigation

31
Q

Act of selecting participants from a particular
population

A

Sampling

32
Q

If total population or sampling frame is less than 50
- If your sample size is less than 30

A

Non-probability

33
Q

also known as expert judgement

A

Purposive sampling

34
Q

everyone has a chance to be picked
o Toss coin
o Computer assisted
o Random numbers
o Fish bowl

A

Simple random sampling

35
Q

K = N/n – same with simple
random but there is a system applied

A

Systematic Sampling

36
Q

inclusion of subgroups
within the population like drug users —- teen and
adults ——male and female
o You group your population to certain traits or
attitude
o Strata

A

Stratified random sampling

37
Q

is a procedure for selecting sample
elements from a fully defined population

A

Sampling method

38
Q

Smaller but hopefully reperesentative collection of
units

A

Sample

39
Q

List from which the potential respondents are drawn

A

Sampling Frame

40
Q

rom theoretical population to the study population to
sampling frame to the sample

A

Sampling Breakdown

41
Q

Techniques used by researchers to
summarize and report data about populations and samples.

  • methods concerned w/ collecting,
    describing, and analyzing a set of
    data without drawing conclusions
    (or inferences) About a large group
A

Descriptive Statistics:

42
Q

methods concerned with the
analysis of a subset of data leading
to predictions or inferences about
the entire set of Data

A

INFERENTIAL
STATISTICS

43
Q

Using tables to organize data.

A

Tabular

44
Q

Using various graphs to visualize data.

A

Graphical

45
Q

: Identifying the positioning of data.

A

Location

46
Q

Displaying the spread of data.

A

Variation

47
Q

Showing how data values are distributed

A

Distribution

48
Q

summarizes a data set by giving a “typical value”
within the range of the data values that describes its location relative to
entire data set.

A

Measure of Location

49
Q

is the smallest value in the data set, denoted as MIN.

A

Minimum

50
Q

is the largest value in the data set, denoted as MAX.

A

Maximum

51
Q

A single value that is used to identify the “center” of the data
– it is thought of as a typical value of the distribution
– precise yet simple
– most representative value of the data

A

MEASURES OF CENTRAL TENDENCY

52
Q

Most common measure of the center
* Also known as arithmetic average

A

MEAN

53
Q
  • Divides the observations into two equal parts
A

MEDIAN

54
Q

in Median If n is odd, the median is the _____________________

A

middle number.

55
Q

in Median If n is even, the median is the average of the ________________

A

2 middle numbers

56
Q

may not be an actual observation in the data set
* can be applied in at least ordinal level
* a positional measure; not affected by extreme values

A

Median

57
Q

occurs most frequently nominal average
* computation of the mode for ungrouped or raw data

A

MODE

58
Q

sampling stability is desired
* other measures are to be computed

A

MEan

59
Q

the exact midpoint of the distribution is desired
* there are extreme observations

A

Median

60
Q

when the “typical” value is desired
* when the dataset is measured on a nominal scale

A

Mode

61
Q

Numerical measures that give the relative position of a data value
relative to the entire data set.

A

Percentiles

62
Q
  • Divide an array into ten equal parts, each part having ten percent of the
    distribution of the data values, denoted by Dj
A

DECILE

63
Q
  • Divide an array into four equal parts, each part having 25% of the
    distribution of the data values, denoted by Qj.
A

QUARTILES

64
Q

________________________ is a single value that is used to describe the
spread of the distribution
* A measure of central tendency alone does not uniquely describe a
distribution

A

measure of variation

65
Q

The difference between the maximum and minimum value in a data set,
i.e. R = MAX – MIN

A

RANGE

66
Q

The larger the value of the range, the more dispersed the observations
are.
* It is quick and easy to understand.
* A rough measure of dispersion.

A

Range

67
Q

most important measure of variation
* square root of Variance
* has the same units as the original data

A

STANDARD DEVIATION (SD)

68
Q
  • Describes the extent of peakedness or
    flatness of the distribution of the data.
A

MEASURES OF KURTOSIS

69
Q

Refers to way observations of a given variable behave in terms of
absolute, relative and cumulative frequencies

A

FREQUENCY DISTRIBUTION

2C PRELIMS (16 decks)

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