M1 Flashcards

(55 cards)

1
Q

the study and use of theory and methods for the analysis of data arising from random processes or phenomena.

A

Statistics

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2
Q

branch of applied statistics directed toward applications in the health sciences and biology.

A

Biostatistics

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3
Q

Process of Applying Statistics – Design experiments and observational studies

A

Making Hypotheses

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4
Q

Process of Applying Statistics – Summary of data

A

Gathering Data

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5
Q

Process of Applying Statistics - Testing of hypotheses

A

Drawing Interferences

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6
Q

Population Based Studies - aims to generate a hypothesis by answering the following questions,
1. What?
2. Who?
3. Where?
4. When?

A

descriptive studies

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7
Q

Example - Incidence Study

A

Descriptive study

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8
Q

Population Based Studies - aims to generate a hypothesis by answering the the “why?” and “how?” questions.

A

Analytic Study

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9
Q

The goal of this study is to measure the association between exposure and outcome

A

Analytic study

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10
Q

Rates are linked to the level of exposure to some agent for the group as a whole

A

Ecological Study

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11
Q

are prepared for illustrating novel,
unusual, or atypical features identified in patients in medical practice, and they potentially generate new research questions.

A

case report

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12
Q

Cross-sectional study, Case-control study, and Cohort study

A

Individual Based - Analytic Study

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13
Q
  • To learn about the characteristics of a population at one point in time
  • Does not use a comparison group
A

Cross-Sectional Study

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14
Q
  • To study rare diseases
  • To study multiple exposures that may be related to a single outcome
A

Case-Control Study

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15
Q

Can be used to find multiple outcomes from a single exposure

A

Cohort Study/ Longitudinal Study/ Follow-up Study

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16
Q

a well-defined group of individuals
who share a common characteristic or experience

A

cohort

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17
Q

This is divided into two branches - Randomized study and non-randomized study

A

Experimental studies

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18
Q

Under this branch is Clinical trial and Control trial

A

Randomized studies

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19
Q

a study in which people are allocated at random (by chance alone) to receive one of several clinical
interventions.

A

Randomized Controlled Trial (RCT)

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20
Q

Someone who takes part in a randomized controlled trial
(RCT) is called

A

Participant or subject

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21
Q
  • seek to measure and compare the outcomes after the participants receive the interventions. Because the outcomes are measure.
  • are quantitative studies.
A

RCT

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22
Q

Under this branch are Quasi-experimental study,
Field trial, and Community trial.

A

Non-Randomized study

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23
Q

Shares similarities with the traditional
experimental design or randomized controlled trial, but it specifically lacks the element of random assignment to treatment or control.

A

Quasi-Experimental Research

24
Q

Applies preventive interventions to healthy individuals.

25
Applies intervention to aggregative units.
Community trial
26
- To provide scientific proof of etiological factors which may permit modification or control of disease. - To provide a method of measuring the effectiveness and efficiency of health services for the prevention, control and treatment of disease and improve the health of the community.
Aims of Experimental Studies
27
- observations of random variables made on the elements of a population or sample. - are the quantities / numbers, or qualities/ attributes measured or observed that are to be collected and or analyzed.
Data
28
Type of data - collect data based on what is seen and heard and infer based on the data collected. Researchers should not interfere with the subjects or variables in any way
Observational data
29
Type of data - produced this by measurement, test method, experimental design. The researcher has control over some variables.
Experimental data
30
The data gathered are presented in paragraph form. Data are written and read. It is a combination of texts and figures.
Textual
31
Method of presenting data using the statistical table
tabular
32
The most effective manner of presenting data since it can be easily understood. Examples are Pie, Bar, Venn, Histogram, Line Diagram and Epidemic curve
Graphical
33
consists of table number and title.
Table heading
34
categories which are found at the left side of the body of the table
stubs
35
the top of the coloumn
Box head
36
main part of the tables
Body
37
any statement or note inserted
footnotes
38
source of the statistics
source notes
39
when used properly, are a powerful tool in quickly and effectively relaying information to your audience.
graphical presentation
40
To examine a relationship between two (nonsequential) variables.
scatterplot
41
It is hard for such a graph not to be informative about the data since all the data points are explicitly represented, hence it is very good for examining data to get a 'feel' for the patterns and identify extreme or unusual values (outliers) for checking or further investigation.
Scatterplot
42
where the x- axis represents some sequential variable like time, or distance along a transect (right, and below). In both cases there is an explicit (spatial or temporal) relationship between adjacent points along the x-axis, and the inclusion of the line makes the pattern of this sequence much clearer.
Line plot
43
The name suggests, have two different y-axes, allowing variables with different scales to be plotted on the same graph. Primarily used in the same sorts of situations as line plots, where you want to compare the pattern of change in two different types of variables.
double y plot
44
Probably the most widely used type of graph in science.
bar chart
45
usually fairly straightforward to produce, and generally are either used to represent means (and appropriate error bars), as in the graph here (right), or counts of some sort, including proportions or percentages. This chart can be presented horizontally or vertically.
bar chart
46
combine features of line plots and stacked bar charts.
area plots
47
are familiar to everyone, much beloved of business graphics packages and the media, but of relatively limited use for scientific figures.
Pie charts
48
is a plot that lets you discover, and show, the underlying frequency distribution (shape) of a set of continuous data. Links to an external site.
HIstogram
49
method of organizing raw data in a compact form by displaying a series of scores in ascending or descending order, together with their frequencies
Frequency table
50
diagram representing mathematical or logical sets pictorially as circles or closed curves within an enclosing rectangle (the universal set), common elements of the sets being represented by the areas of overlap among the circles.
Venn diagram
51
A visual display of the onset of illness among cases associated with an outbreak.
Epidemic curve
52
is used to estimate the extent of the disease in the population
survey study
53
designed to monitor or detect specific diseases
surveillance study
54
investigate association between an exposure and a disease outcome. They rely on “natural” allocation of individuals to exposed or non-exposed groups.
Observational Study
55
also investigates the association between an exposure, often therapeutic treatment, and disease outcome individuals are “intentionally” placed into the treatment groups by the investigators
Experimental Study