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PRELIMS > CPHM: LESSON 2 Introduction to Biostatistic > Flashcards

CPHM: LESSON 2 Introduction to Biostatistic Flashcards

1
Q

•…application of statistical methods to the life sciences like biology, medicine and public health”…

A

Biostatistics

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2
Q

two Branches of Statistics

A

Descriptive Statistics and Inferential Statistics

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3
Q

Statistical techniques for summarizing and presenting data in a form that will make them easier to analyze and interpret

A

Descriptive Statistics

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4
Q

Concerned in making estimates, predictions, generalizations, and conclusions about a target population based on information from a sample
• Estimation
• Hypothesis testing

A

• Inferential Statistics

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5
Q

• Demographic
• Health Status
• Health Resources
• Health-related Socio-economic Environmental Factors

A

Statistical Data

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6
Q

Used to describe the variety and frequency of past outcomes under similar conditions as a way of predicting what should happen in the future

A

Probability

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7
Q

used to express the degree of probability or improbability of a certain result in an experiment.

A

P value

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8
Q

Expresses the probability that the observed result could have occurred by chance alone.

A

P value

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9
Q

• This is a range of values within which the true result probably falls.

A

Confidence Interval

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10
Q

the lower the likelihood of random error.

A

Confidence Interval

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11
Q

Are often expressed as margins of error, as in political polling, when a politician’s support might be estimated at 50 percent. The confidence interval would be 47% to 53%

A

Confidence Interval

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12
Q

• While p values and confidence intervals are useful concepts in deciding how seriously to take an experimental result, it is wrong to place too much confidence in an experiment just because it yields a low p value or a narrow confidence interval.

A

True

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13
Q

measurement of a characteristics

A

Variable

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14
Q

variables whose categories are simply used as labels to distinguish one group from another

A

Qualitative

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15
Q

numerical representation of the categories are for labeling/coding and NOT for comparison

A

Qualitative

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16
Q

sex, religion, place of residence,
Disease status

A

Qualitative

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17
Q

values indicate a quantity or amount and can be expressed numerically

A

Quantitative

18
Q

values can be arranged according to magnitude

age, height, weight, blood pressure

A

Quantitative

19
Q

a classificatory scale where the categories are used as labels only
example: sex, race, blood group, patient ID

A

Nominal

20
Q

used for categories which can be ordered or ranked
Example: likert scale, psychosocial Scale

A

ordinal

21
Q

same characteristics as ordinal; zero point is arbitrary and does not mean absence of the characteristic

Example:temperature, IQ

A

Interval

22
Q

same characteristics as ordinal; a meaningful zero point exist
example: weight, BP, height, doctor visits

A

Ratio

23
Q

It refers to the arrangement of any data in an orderly sequence, so that they can be presented concisely and compactly and so that they can be understood easily.

A

TABULATION

24
Q

• Data are grouped according to some scale of classification, where the sum of the entries is equal to
• the total. The figures may either be in equal numbers, in percent, or in both. The scales used may be qualitative, quantitative, or both.
• A frequency distribution shows the number of observations falling into each of several ranges of values.
Frequency distributions are portrayed as frequency tables, histograms, or polygons.

A

Frequency distribution

25
Q

used to compare two or more frequencies

A

Correlation data

26
Q

some variable changes over a while is the one being presented

A

Time series data

27
Q

it should state the objective of the table. It should clearly, briefly and comprehensively what the figures in the body of the table stand for. How the data are classified, where and when obtained

A

Title

28
Q

indicate the basis of classification of the rows or horizontal series of figures

A

Stubs

29
Q

indicate the basis of classification of the columns or vertical series of figures.

A

Column headings

30
Q

this is made up of the figures filling the cells or compartments brought about by the coordinates of rows and columns

A

Body of the table

31
Q

refer to the column totals and row totals

A

Marginal Totals

32
Q

indicate the source of information

A

Footnote

33
Q

• The purpose is to convey a simpler idea of what the statistical table contains.
• Statistical graph either a series of lines joined together, or bars or enclosed areas, drawn to represent certain statistical information under consideration.
• Intended for comparison, to show correlation, or simply for data presentation
• Primary tools for presentation and analysis.

A

Graphing

34
Q

Parts of a Graph: indicate clearly and briefly what the figures in the body of the graph stand for, how the data were classified, and where and when obtained. This is placed at the bottom of the graph, preceded by number for easy reference.

A

title

35
Q

a graph has 2 axes, the vertical and the horizontal:

A

Axis

36
Q

true or false: Each represents separate scales of classification corresponding to the row and column headings of the table being graphically presented.

A

true

37
Q

true or false: • One of the axes is always quantitative scale while the other is either qualitative or quantitative scales.

A

true

38
Q

this is needed when one is drawing more than one graph in a graphing space. This clarifies to what particular item each of the graph refers. It is placed either at the bottom of the graph or as close as possible to the figures being identified.

A

Legend

39
Q

these are the lines, bars or figures drawn within the graphing

A

Body of the graph

40
Q

there are two kinds of scales used, the qualitative and the quantitative which may discontinuous variety (counts) or continuous (measurement)

A

Frequency Distribution

41
Q

numbers (count) or raters (measurements) plotted over a given time period

A

trend

42
Q

maybe either of the two

A

Correlation data

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