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Biostatistics & Epidemiology > Nature of Statistics and Data Processing > Flashcards

Nature of Statistics and Data Processing Flashcards

1
Q

Totality of methods and treatments employed in the collection, description, and analysis of numerical data. The purpose of descriptive statistics is to tell something about a particular group of observations.

A

Descriptive Statistics

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2
Q

Logical process from sample analysis to a generalization or conclusion about a population.

It is called statistical inference or inductive statistics.

A

Inferential Statistics

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3
Q

Consist of all the members of the group about which one wants to draw a conclusion.

A

Population

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4
Q

Portion or part of the population used to describe the whole group.

A

Sample

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5
Q

4 Random Sampling Technique

A
  1. Simple random sampling
  2. Systematic sampling
  3. Stratified random sampling
  4. Cluster sampling
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6
Q

Whose members had an equal chance of being selected from the population; it is also called probability sampling.

A

Random Sampling Technique

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7
Q

It is a process of selecting sample size in the population via random numbers or through lottery and not on a systematic pattern.

[random sampling technique]

A

Simple random sampling

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8
Q

It is a process of selecting a kth element in the population until the desired number of subjects or respondents is attained.

[random sampling technique]

A

Systematic sampling

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9
Q

A method of sampling that involves the division of a population into smaller sub-groups known as strata.

[random sampling technique]

A

Stratified random sampling

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10
Q

It is a process of selecting clusters from a population which is very large or widely spread out over a wide geographical area.

[random sampling technique]

A

Cluster sampling

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11
Q

Sampling procedure where samples selected in a deliberate manner with little or no attention to randomization; it is also called non-probability sampling.

A

Non-random Sampling Process

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12
Q

It is a process of selecting a group of individuals who are available for study.

[non-random sampling]

A

Convenience sampling

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13
Q

It is a process of selecting based from judgment to select a sample which the researcher believed, based on prior information, will provide the data they need, it is also called as judgment sampling.

[non-random sampling]

A

Purposive Sampling

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14
Q

It is applied when an investigator survey collects information from an assigned number, or quota of individuals from one of several sample units fulfilling certain prescribed criteria or belonging to one stratum.

[non-random sampling]

A

Quota Sampling

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15
Q

It is a technique in which one or more members of a population are located and used to lead the researchers to other members of the population.

[non-random sampling]

A

Snowball Sampling

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16
Q

It is a technique when samples are composed of respondents who are self-selected into the study/survey. Most of the time, samples have a strong interest in the topic of the study.

[non-random sampling]

A

Voluntary Sampling

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17
Q

It is a technique when the researcher relies on his/her personal/sound judgment in choosing to participate in the study or the sample selected is based on the opinion of an expert.

[non-random sampling]

A

Judgement Sampling

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18
Q

Information gathered from the sample/population.

A

Data

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19
Q

Mutually exclusive and exhaustive; meaning it is used to differentiate classes or categories for purely classification or identification.

[noir]

A

Nominal

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20
Q

Weakest form of measurement.

[noir]

A

Nominal

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21
Q

Used in ranking. It is somewhat stronger form of measurement, because an observed value classified into one category is said to possess more of a property being scaled than does observed value classified into another category.

[noir]

A

Ordinal (order)

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22
Q

They provide meaningful insights into attitudes, preferences, and behaviors by understanding the order of responses.

[noir]

A

Ordinal

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23
Q

Used to classify order and differentiate between classes or categories in terms of degrees of differences.

[noir]

A

Interval

24
Q

Temperature and time often make use of this type of measurement, enabling precise comparisons and calculations.

[noir]

A

Interval

25
Q

Great for research in fields like science, engineering, and finance, where you need to use ratios, percentages, and averages to understand the data.

[noir]

A

Ratio

26
Q

Concerned with editing, coding, classifying, tabulating and charting and diagramming research data.

A

Data processing

27
Q

6 Stages of Data Processing

A
  1. Data collection
  2. Data preparation
  3. Data input
  4. Data processing
  5. Data output
  6. Data storage and report writing
28
Q

First step in data processing.

[stages of data processing]

A

Data collection

29
Q

It is important that the data sources available are trustworthy so the data collected is of the highest possible quality.

[stages of data processing]

A

Data collection

30
Q

It enters once the data is collected.

[stages of data processing]

A

Data preparation

31
Q

It is often referred to as “pre-processing”, this is where raw data is cleaned up and organized for the following stage of data processing.

[stages of data]

A

Data preparation

32
Q

The purpose of this stage is to eliminate incomplete, or incorrect data and begin to create high quality data.

[stages of data processing]

A

Data preparation

33
Q

The clean data is then entered.

[stages of data processing]

A

Data input

34
Q

The first stage in which raw data begins to take the form of usable information.

[stages of data processing]

A

Data input

35
Q

During this stage, the data inputted is being processed for interpretation.

[stages of data processing]

A

Data processing

36
Q

In this stage at which data is finally usable to non-data scientists.

[stages of data processing]

A

Data output

37
Q

It is translated to readable, and often in the form of graphs, videos, images or plain text.

[stages of data processing]

A

Data output

38
Q

Final stage of data processing, it is stored for future use. Stages of data processing.

[stages of data processing]

A

Data storage

39
Q

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

A

Data coding

40
Q

4 types of Codes

A
  1. Field Code
  2. Bracket Code
  3. Factual Code
  4. Pattern Code
41
Q

Actual value or information given by the respondent.

[types of code]

A

Field code

42
Q

Recorded as a range of values rather than actual values.

[types of code]

A

Bracket code

43
Q

Codes are assigned to a list of categories of a given variable.

[types of code]

A

Factual code

44
Q

Applicable for questions with multiple responses.

[types of code]

A

Pattern code

45
Q

A document which contains a record of all codes assigned to the responses to all questions in the data collection forms.

A

Coding Manual

46
Q

Inspection and correction of any errors or inconsistencies in the information collected.

A

Data Editing

47
Q

Entering the data/responses in a spreadsheet

  • MS Excel
  • MS Access
  • Epi Info
A

Data Encoding

48
Q

2 Types of Editing

A
  1. Field editing
  2. Central editing
49
Q

Reviewing the accomplished data collection forms.

[types of editing]

A

Field editing

50
Q

Decoding of abbreviations or special symbols.

[types of editing]

A

Field editing

51
Q

Making callbacks/messages for verification /clarification of incomplete answers.

[types of editing]

A

Field editing

52
Q

Checking of inconsistencies and incorrect entries after receiving the questionnaire from the field.

[types of editing]

A

Central editing

53
Q

Checking of encoded data.

[types of editing]

A

Central editing

54
Q

Formula used to determine how much of the population will be included as part.

A

Slovin’s Formula

55
Q
A

Biostatistics & Epidemiology (19 decks)

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