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MIDTERMS > RESEARCH 115 > Flashcards

RESEARCH 115 Flashcards

1
Q

DATA MANAGEMENT AND ANALYSIS

A

QUALITATIVE

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2
Q

It is a non-numerical organization & interpretation of data to discover themes or patterns that are found in the field notes, interviews, recorded conversations, etc.

A

QUALITATIVE ANALYSIS

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3
Q

characteristics of qualitative analysis

A
  1. No universal rule
  2. Thick descriptions
  3. Enormous work
  4. Reduces data for reporting purposes
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4
Q

if it will describe the phenomenon in detail, specific, & contains all descriptions needed by the readers to understand phenomenon

A

THICK DESCRIPTION

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5
Q

should contain INFORMATION, INTENTION, & MEANING & SUBSEQUENT ACTIONS that can evolve from the phenoemna

A

THICK DESCRIPTION

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6
Q

FLOWCHARTS OF THE STUDY (qualitative)

A

Identification of the study
↓
Participants inclusion criteria
↓
Data Gathering Method
↓
TRANSCRIPTION OF INTERVIEWS
↓
Validating
↓
DATA ANALYSIS
↓
Documentation
↓
Dissemination of Findings

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7
Q

STEPS (qualitative)

A
  1. Read thoroughly & repeatedly-decipher meanings
  2. Clustering of similar responses
  3. Formulate themes & subthemes
  4. Construct a major theme & subtheme
  5. Presentation of themes & subthemes to participants
  6. Formulation of conceptual map after the participants have approved the themes
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8
Q

STRATEGIES IN ANALYZING OR HANDLING QUALITATIVE DATA:

A
  1. PRE-ANALYSIS ACTIVITIES
  2. ANALYSIS ACTIVITIES
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9
Q

record immediately relevant data

A

PRE-ANALYSIS ACTIVITIES

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10
Q

immersion

A

ANALYSIS ACTIVITIES

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11
Q

re-reading in search of themes

A

ANALYSIS ACTIVITIES

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12
Q

THEMATIC ANALYSIS

A

Researcher tries to RECOVER and UNCOVER what is embodied in the content

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13
Q

THEME

A

A phrase that described the fundamental meaning (essence) or significance in a selected portion in a narrative data

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14
Q

Someone who uses ______ makes SPECIFIC OBSERVATIONS and THEN DRAWS A GENERAL CONCLUSION

A

INDUCTIVE REASONING

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15
Q

is a SPECIFIC CONCLUSION FOLLOWS A GENERAL THEORY

A

DEDUCTIVE REASONING

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16
Q

Every quiz has been easy. Therefore, the test will be easy.

A

example of INDUCTIVE REASONING

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17
Q

All students in this class play guitar. SAM IS A STUDENT OF THIS CLASS. -Therefore, Sam plays guitar.

A

example of DEDUCTIVE REASONING

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18
Q

Thematic analysis includes:

A
  1. Deductive Process
  2. Inductive Process
    *Integration process
  3. Eclectic Approach
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19
Q

the researcher develops category based on subthemes that will represent each subproblems

A

Deductive Process

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20
Q

the researcher tackles one category at a time

A

Inductive Process

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21
Q

related them to subproblems

A

Inductive Process

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22
Q

use of metaphors or figures of speech

A

Inductive Process

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23
Q

study of relationship or linkages between themes within the subproblems or across the different subproblems

A

Integration process

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24
Q

blending of independent and dependent variables

A

ECLECTIC APPROACH

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25
Q

REDUCING DATA

A

ECLECTIC APPROACH

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26
Q

INTERPRETATION OF QUALITATIVE DATA

A

A. EMIC PERSPECTIVE
B. ETIC PERSPECTIVE

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27
Q

‘Insider’s View’ (Participant)

A

EMIC PERSPECTIVE

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28
Q

The way the members describe their own experiences or perceive themselves

A

EMIC PERSPECTIVE

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29
Q

‘Outsider’s View’

A

ETIC PERSPECTIVE

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30
Q

The way the researcher describe experiences of the participants

A

ETIC PERSPECTIVE

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31
Q

Data analysis

A

QUANTITATIVE

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32
Q

separation of data into parts for the purpose of answering research questions & communicating the answers to others

A

DATA ANALYSIS

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33
Q

depend on specific question, research design, data collection method, & levels of measurement

A

DATA ANALYSIS

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34
Q

2 types/branches of DATA ANALYSIS (quantitative)

A
  1. Descriptive Analysis
  2. Inferential Analysis
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35
Q

use to describe individual variables of the study

A

DESCRIPTIVE ANALYSIS

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36
Q

find out the relationship or difference of the variables under study

A

INFERENTIAL ANALYSIS

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37
Q

2 methods in research

A

Qualitative and Quantitative

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38
Q

2 design in research

A

Experimental and Non-experimental

39
Q

4 types of descriptive analysis

A

Frequency
Percentage
Mean, Median, Mode
Standard Deviation

40
Q

2 types of inferential analysis

A

Parametric
Non-parametric

41
Q

types of PARAMETRIC (Homogeneity)

A

T-test
Annova
Pearson Moment Correlation Coefficient

42
Q

independent
dependent

A

T test

43
Q

2/more respondents

A

Anova

44
Q

not quality unlike parametric

A

non-parametric

45
Q

Steps in testing hypothesis:

A
  1. States the Ho (Null hypothesis)
  2. Select a level of significance (0.05)
  3. Determine the statistical formula to be used
  4. Identify the critical values or tabular values
  5. Calculate value and apply the test
  6. Compare the values
  7. Interpretation
46
Q

2 types of level of significance:

A

a. Type 1error (Alpha error)
b.Type ll error (Beta error)

47
Q

the researcher rejects a Ho that is really TRUE

A

Alpha error

48
Q

failure of a researcher to reject a Ho which is really FALSE

A

Beta Error

49
Q

CV>/=TV

A

Reject Ho- SIGNIFICANT

50
Q

CV</=

A

Accept Ho- NOT SIGNIFICANT

51
Q

4 Levels of interpretation

A

LEVEL I
LEVEL II
LEVEL III
LEVEL IV

52
Q

giving meaning to the numerical data contained in the table

A

LEVEL I

53
Q

describe statistical formula

A

LEVEL II

54
Q

possible reasons or effects of data

A

LEVEL III

55
Q

Retrieve studies presented in RRL

A

LEVEL IV

56
Q

overall, general

A

level I

57
Q

highest & lowest

A

level II

58
Q

implication

A

level III

59
Q

collaboration

A

level IV

60
Q
  • means
A

SIGNIFICANT

61
Q

2 formula

A

Fiszer’s
Scheffe’s

62
Q

natural, naturalistic

A

QUALITATIVE

63
Q

deductive, general to specific

A

QUANTITATIVE

64
Q

inductive, specific to general

A

QUALITATIVE

65
Q

No matter how well the objectives are written, or how clever the items, the quality and usefulness of an examination is predicated on ____ & ____.

A

VALIDITY and RELIABILITY

66
Q

It refers to the degree which the tool measures, what it is intended to measure

A

VALIDITY

67
Q

It refers to whether the instrument or scale is quantifying what it claims to

A

VALIDITY

68
Q

Ex. “Weight” scale measure body weight and it is valid.

A

VALIDITY

69
Q

*Means “repeatability” or “consistency”
*It is the ability to an instrument to consistently measure what it is suppose to measure
*A measure is considered reliable if it would give us the same result over and over again (assuming that what we are measuring isn’t changing!)

A

RELIABILITY

70
Q

Levels of Measurement

A
  1. NOMINAL
  2. ORDINAL
  3. INTERVAL
  4. RATIO
71
Q

The nominal level of measurement applies to data that consist of names, labels, or categories. There are no implied criteria by which the data can be ordered from smallest to largest.

A

NOMINAL

72
Q

Ex.
Gender
Nationality
Phone number
Course
Responses: Yes/No

A

NOMINAL

73
Q

The ordinal level of measurement applies to data that can be arranged in order. However, differences between data values either cannot be determined or are meaningless.

A

ORDINAL

74
Q

Ex.
Satisfaction Level
IQ Level
Self-Esteem Level
Degree of Pain
Monthly Income Classification

A

ORDINAL

75
Q

The interval level of measurement applies to data that can be arranged in order. In addition, differences between data values are meaningful. It has no inherent (natural) zero starting point.

A

INTERVAL

76
Q

Temperature
Year
IQ Score

A

INTERVAL

77
Q

The ratio level of measurement applies to data that can be arranged in order. In addition, both differences between data values and ratios of data values are meaningful. Data at the ratio level have a true zero.

A

ratio

78
Q

Age
Height
Test Score
Salary
Distance

A

ratio

79
Q

The ____ is the probability of rejecting Ho when it is true.

A

Level of Significance

80
Q

This is the probability of a type I error, denoted by 𝛼.

A

Level of Significance

81
Q

A ______ is a test statistic value beyond which we reject the null hypothesis; often called a cutoff.

A

Critical Value

82
Q

The ______ refers to the area in the tails of the comparison distribution in which we reject the null hypothesis if our test statistic falls there.

A

critical region

83
Q

Ho is true, the probability that the test statistic will take on values as extreme assumings or more extreme than the observed test statistic (computed from sample data) is called the _____of the test.

A

Probability Value (p-value)

84
Q

In statistical tests, a _______ result means that the null hypothesis has been rejected, which means that the result is very unlikely to have occurred merely by chance.

A

significant

85
Q

Steps in Hypothesis Testing

A
  1. State the null and alternative hypothesis.
  2. Set the level of significance.
  3. Compute the test statistic.
  4. Determine the critical value or p-value.
  5. Make the decision.
86
Q

______ if the absolute computed value is greater than or equal to the absolute tabular/critical value.

|Computed Value| ≥ |Critical Value|

A

Reject Ho

87
Q

____ if the absolute computed value is less than the absolute tabular value.

|Computed Value| < |Critical Value|

A

Do not reject Ho

88
Q

____ if the p-value is less than or equal to the level of significance.

        p-value ≤ 𝜶
A

Reject Ho

89
Q

_____ if the p-value is greater than the level of significance.

                p-value > 𝜶
A

Do not reject Ho

90
Q

needs to provide a brief but comprehensive summary of the contents of your paper.

A

abstract

91
Q

It provides an overview of the paper and helps readers decide whether to read the full text.

A

abstract

92
Q

Limit your abstract to ______ words.

A

250

93
Q

_____ address essential paper elements, such as the following:
* research topic
* population
* method
* application of results or findings

A

Keywords

94
Q

written one line below the abstract
indented (like a regular paragraph)
italic (but not bold)

A

Keywords

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