Data Management pt. 1 Flashcards

1
Q

2 types of statistics

A

Descriptive and inferential

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2
Q

Collection, organization, summary, and presentation of data. Beginning
i.e. measures of location, measures of variability, skewness and kurtosis

A

Descriptive

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3
Q

interpretation and analysis of data.
conclusion is drawn based on the subset of the population
i.e hypothesis testing and regression analysis

A

Inferential

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4
Q

the characteristic that is being studied
varies across individuals or objects

A

Variables

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5
Q

data that can assume values that manifest the concept of attributes
AKA categorical data
Cannot be measured

A

Qualitative Variables

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6
Q

finite number of possible values
CAN be counted but CANNOT be measured
Whole numbers

A

Discrete Variables

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7
Q

data from counting or measuring
numerical data representing numerical value

A

Quantitative Variables

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8
Q

infinite number of probable values, can be selected within a given rage
CAN be measured but CANNOT be counted

A

Continuous Variables

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9
Q

Levels of Measurement

A

Nominal, ordinal, ratio and interval (NORI)

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10
Q

used to label or classify variables using letters, words, and alpha numeric symbols. No particular order.

A

Nominal

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11
Q

represents discrete and ordered units, follows a natural order

A

Ordinal

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12
Q

tells the distances between measurements in addition to the classification and ordering

no true zero point

A

Interval

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13
Q

most informative as it combines the first three levels,
order units that have the same difference

A

Ratio

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14
Q

Examples of ratio

A

kelvin, height, weight, length, and time/duration

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15
Q

steps in statistical inquiry or investigation

A

Defining the problem
Collection/ gathering of info or data
Organization/presentation of data
Interpretation of data

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16
Q

2 types of sampling methods

A

Probability and Non-Probability

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17
Q

equal chance of getting selected, includes entire population
lottery, fishbowl method, and table of random numbers

A

Simple Random Sampling

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18
Q

everyone is assigned a number and individuals are chosen at regular intervals.

A

Systematic Sampling

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19
Q

populations -> subgroups (strata) based on a relevant characteristic not all members are included though
(e.g. age, income, job role, gender …)

A

Stratified Random Sampling

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20
Q

area sampling
population -> subgroups but all members are included

A

Cluster Sampling

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21
Q

most accessible individuals to the researcher

A

Convenience sampling

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22
Q

can be biased as some people are more likely to volunteer than others

A

Voluntary Response Sampling

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23
Q

individuals are handpicked by the researcher, deemed most useful for the research

A

Purposive Sampling

24
Q

finding respondents through recommendations from previous participants

A

Snowball Sampling

25
Q

2 types of sources

A

Primary and secondary sources

26
Q

raw, first-hand evidence
i.e. interview, statistical data, and artworks

A

Primary

27
Q

second-hand information and commentary from other researchers

A

Secondary sources

28
Q

Data collection techniques

A

Interviews
Projective technique
Delphi Technique
Focus Groups
Questionnaires

(PIdeFoQue)= Putang Ina The Fuck?

29
Q

researchers ask qs by direct interviews or means of mass communications

A

Interviews

30
Q

indirect interview, respondents know why they’re being asked but the q is incomplete, to be filled in with their opinions feelings, and attitudes

A

Projective Technique

31
Q

each expert answers based on their field of specialization, then their responses are consolidated into one opinion.

A

Delphi Technique

32
Q

6-12 people with a moderator discussing one topic / issue

A

Focus Groups

33
Q

series of questions either open or close-ended related to the matter at hand.

A

Questionnaires

34
Q

Presentation of Data

A

Textual, Tabular, Graphic

35
Q

in narrative/ paragraph form
combines text and figures in a statistic

A

Textual Presentation

36
Q

data is in tables, more comprehensible comparison of figures or report

A

Tabular Presentation

37
Q

presented in visual or pictorial form
clear view of relationships through pics and colored maps

A

Graphic Presentation

38
Q

Types of Graphic Presentation

A

Line Graph, Bar Graph, Circle Graph/ Pie Chart, and Pictograph/Pictogram

39
Q

shows a trend over a period

A

Line Graph

40
Q

for comparison of simple magnitude
can be horizontal or vertical

A

Bar Graph

41
Q

circle divided into parts, sizes are proportional to the magnitude/ percentages they represent
shows component parts of a whole

A

Circle Graph / Pie Chart

42
Q

makes use of pictorial symbols to indicate data with a legend

A

Pictograph / Pictogram

43
Q

tabular arrangement of data with its classification / grouping according to magnitude / size

A

Frequency Distribution

44
Q

Number of given

A

n

45
Q

end numbers of a class
highest and lowest value

A

Class Limit

46
Q

Total number of classes
Sturge’s formula and Slovin’s formula

A

Number of Classes = K

47
Q

“true” class limits defined by upper and lower boundaries
lower boundary can be determined by ave of the upper limit of a class and lower limit of the next class
Add 0.5 to upper limit and subtract 0.5 to the lower limit

A

Class Boundaries =CB = +/- 0.5

48
Q

ave of the lower and upper limits of each class

A

Class Mark = midpoint = x

49
Q

difference of upper and lower boundaries of each class.
affected by the nature of data and the number of classes

A

Class Interval = range = r = UL-LL

50
Q

the width of each class interval

A

Class size = LL+ R/K

51
Q

adding frequencies from highest to lowest

A

“Less Than” (<cf)

52
Q

adding frequencies from lowest to highest

A

“More Than” (>cf)

53
Q

Relative frequency = %RF

A

(f/n)(100) = %RF

54
Q

Cumulative Percentage (%>or <cf)

A

(>cf or <cf / n)(100) = %cf

55
Q

When intervals are uniform, width of the bar must also be uniform

x axis = class boundary (CB)
y axis = frequency (F)

A

Histogram

56
Q

Constructed broken line curve

x axis = midpoint (x)
y axis = frequency (F)

A

Frequency Polygon