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BIOE PRELIM > Nature of Biostatistics > Flashcards

Nature of Biostatistics Flashcards

1
Q

science dealing with collection, organization, analysis and interpretation of numerical data.

A

statistics

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2
Q

art of summarazing data so that non-statistician can understand it.

A

statistics

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3
Q

special branch of stats which deals with quantitative and qualitative aspects of vital phenomena.

A

biostatistics

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4
Q

data required in planning, administration, and evolution of health programs

A

health statistics

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5
Q

N

all members of specified group

A

population

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6
Q

n

subset of population

A

sample

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7
Q

measure of characteristics of population

A

parameter

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8
Q

value of characteristics that remains the same from person to person, from time to time or place to place

A

constant

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9
Q

characteristics take on different values

A

variable

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10
Q

methods of summarizing and presenting data

A

descriptive statistics

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11
Q

computation of measures of central tendency and variability

A

descriptive statistics

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12
Q
A
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13
Q

tabulation and graphical presentation

A

descriptive statistics

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14
Q

methods of arriving at conclusions and generalizations about a target population based on information from a sample

A

inferential statistics

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15
Q

estimation of parameters and hypothesis testing

A

inferential statistics

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16
Q

type of data

according to source

A
  • primary data
  • secondary data
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17
Q
A
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18
Q

categories of data

types of variables

A
  • qualitative
  • quantitative
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19
Q

descriptions/labels to distinguish one group from another

A

qualitative

20
Q

can be measured and ordered according to quantity or amount and expressed numerically.

A

quantitative

21
Q

types of quantitative data

A
  • discrete
  • continuous
22
Q

can assume a finite or countable number of values

A

discrete

23
Q

can assume an infinity or other possible values

A

continuous

24
Q

scale of measurement of variables

A
  • nominal
  • ordinal
  • interval
  • ratio
25
Q
  • used for names or identifiers of category
  • always qualitative
  • does not represent any amount
A

nominal

26
Q
  • represents an ordered series of relationships
  • may be qualitative of quantitative
A

ordinal

27
Q
  • does not have true-zero value starting point
  • always quantitative
A

interval

28
Q
  • modified interval level which includes zero as a starting point
  • quantitative
A

ratio

29
Q

systematic procedure to ensure that the information/data gathered are complete, consistent and suitable for analysis

A

data processing

30
Q

data processing

A
  • coding
  • encoding
  • editing
31
Q

conversion of verbal/written information into numbers which can be more easily encoded, counted, tabulated

A

data coding

32
Q

types of codes

A
  • field
  • bracket
  • factual
  • pattern
33
Q

actual value or info given by respondent

A

field code

34
Q

recorded as range of values rather than actual values

A

bracket values

35
Q

codes assigned to a list of categories of given variable

A

factual code

36
Q

applicable for questions with multiple responses

A

pattern code

37
Q

minimum information that must be included in coding manual:

A
  • variable name
  • variable description
  • coding instructions
38
Q

document contain a record of all codes assigned to the responsed to all questions in data collection forms

A

coding manual

39
Q

Entering the data/responses in a
spreadsheet.

A

data encoding

40
Q
  • Inspection and correction of any errors or
    inconsistencies in the information collected.
  • During data collection, encoding, before data
    analysis
A

data editing

41
Q

types of editing

A

field
central

42
Q

Reviewing the accomplished data
collection forms decoding of abbreviations or special
symbols making callbacks/messages for
verification/clarification of incomplete answers.

A

field editing

43
Q
  • Make corrections as early as possible.
  • Reduce non-response or incomplete answers.
  • Eliminate inconsistencies, incorrect info.
  • Make the entries clear, legible and
  • Comprehensive.
  • Prepare data for analysis.
A

importance of data editing

44
Q
  • Check for duplicate entries.
  • Check the totals of each variable if the same as
    with the sample size.
  • For qualitative data, check if categories are
    consistent with what is specified in the coding
    manual.
  • For quantitative data, check the minimum and
    maximum if they are logical given the possible
    values of variable.
A

what to check when editing data

45
Q
A

BIOE PRELIM (7 decks)

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