PRACRES ALL Flashcards
(133 cards)
1
Q
A technique which the researcher uses to gather and generate data about the subjects of their study.
A
Method
2
Q
Measurement tools designed to obtain data on a topic of interest from research subjects
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Research Instrument
3
Q
Analysis of data that have originally been collected either for a different purpose or by a different researcher or organization.
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Secondary Analysis
4
Q
Research that involves searching for and extracting information and evidence from original archives.
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Archival Research
5
Q
Conversations that are designed to obtain specific kinds of information.
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Individual Interview
6
Q
Types of Interview: can be in the form of normal conversations of a freewheeling exchange of ideas.
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Unstructured
7
Q
Types of Interview: the conduct of questioning follows a particular progression and has a well-defined content.
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Structured
8
Q
Types of Interview: there is a specific set of questions but there are also follow up questions that are not included in the list of questions.
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Semi-structured
9
Q
A list containing a set of structured questions to serve as a guide for collecting information or data during the actual interview.
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Interview Schedule
10
Q
Interviews conducted with several respondents simultaneously
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Group Interview
11
Q
Selected by researchers according to specific criteria
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Focus Groups
12
Q
Makes use of ratings or numerical rankings
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Observation Checklist
12
Q
Belongs to a group that exists independently of the study.
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Natural Groups
13
Q
Resembles interview schedules but are less restrictive in structure to allow the respondents a more free and dynamic exchange of ideas.
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Topic Guides
14
Q
Data collection technique in which the researcher makes use of all the five senses in examining the subject in a natural setting or naturally occurring situation.
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Observations
15
Q
Allows for more general descriptive documentation
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Observation Guides
16
Q
Research methods by which researchers create controllable environments to test hypothesis
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Laboratory Experiments
17
Q
Refers to research that is undertaken in the real world, where the confines of a laboratory setting are abandoned in favour of a natural setting.
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Field Studies
18
Q
Study of the behaviour of systems in using programs run on a computer.
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Computer Modelling/Simulation
19
Q
Refers to the collection, recording and analysis of information on a particular subject, an area or a group of people.
A
Survey
20
Q
Implies a form containing a list of ready-made questions, delivered to people for obtaining statistical information.
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Questionnaires
21
Q
involves the separation of medicinally active portions of plant or animal tissues from the inactive or inert components by using selective solvents in standard extraction procedures.
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Extraction
22
Q
It is a liquid or a suitable solvent chosen for an effective extraction process.
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Menstruum
23
Q
It is an insoluble or inert drug material that is left behind at the end of the extraction process
A
Marc
24
a device used in chemical laboratories for the efficient and gentle removal of solvents from samples by evaporation.
Rotary Evaporation
24
In this process, the whole or coarsely powdered crude the drug is placed in a stoppered container with the solvent and allowed to stand at room temperature for a period of at least 3 days with frequent agitation until the soluble matter has dissolved.
Maceration
24
It is the mixture of both the extracted drug material and the solvent of extraction.
Micelle
25
form of maceration in which gentle heat is used during the process of extraction. It is used when moderately elevated temperature is not objectionable
Digestion
26
prepared by macerating the crude drug for a short period of time with cold or boiling water.
Infusion
27
In this process, the crude drug is boiled in a specified volume of water for a defined time; it is then cooled and strained or filtered.
Decoction
28
A volume of the microbial inoculum is applied evenly across the surface of the agar plate to inoculate it.
Agar Well Methods
29
A standard inoculum of the test microorganism is used to inoculate agar plates. Following that, 6mm-diameter filter paper discs are placed on the agar surface, each containing the test substance in the desired concentration.
Disk Diffusion Method
30
Agar-plots or cylinders are cut aseptically using a sterile cork borer from the desired strain and placed on another plate that has already been injected with the test microbe.
Agar Plug Method
31
The poisoned food approach is typically used to assess a substance's ability to fight mold.
Poisoned Food Method
32
Dosing by oral gavage involves passing a feeding needle through the mouth and into the esophagus.
Mouse Oral Gavage
33
Involves amputating less than 2 mm of mice tail. Blotting of blood using filter paper until bleeding ceased.
Tail Bleeding Time Test
34
The basic principle is that each compound absorbs or transmits light over a certain range of wavelengths.
Spectrophotometry
35
mechanical test measuring the maximum amount of compressive load a material can bear before fracturing.
Compressive Strength Test
36
common materials test in which the test sample is subjected to a controlled tension load until it breaks.
Tensile Strength Test
37
Basically means “measure what is intended to be measured”
Validity
38
is the extent to which a study establishes a trustworthy cause-and-effect relationship between a treatment and an outcome.
Internal Validity
39
refers to how well the outcome of a study can be expected to apply to other settings.
External Validity
40
The extent that measurement instrument items linguistically and analytically look like what is supposed to be measured.
Face Validity
41
The extent that measurement instrument items are relevant and representative of the largest construct.
Content Validity
42
The extent that measures of different constructs diverge or minimally correlate with one another.
Construct Discriminant Validity
43
The extent that different measures of the same construct converge or strongly correlate with one another.
Construct Convergent Validity
44
The extent that a measure predicts another measure.
Criterion Predictive Validity
45
The extent that a measure simultaneously relates to another measure that it is supposed to relate to.
Criterion Concurrent Validity
46
The extent that a measure is related to the scores on another, already established in the past.
Criterion Postdictive Validity
47
Refers to the consistency of a measure
Reliability
48
Can be measured using Test-retest correlation
Test-retest Reliability
49
Can be measured by split-half, using Kuder-Richardson test (Score, mean, and SD is needed)
Internal Consistency
50
Can be measured by Cohen’s Kappa or Fleiss Kappa
Inter-Rater Reliability
51
Selection of people for a study may result in unintended differences related to the variable (Selection Bias)
Subject Characteristics
52
Data collection or intervention in specific locations may lead to alternative result interpretations.
Location Threat
53
Loss of subjects in a study may introduce bias and affect the study outcome.
Mortality Threat
54
Changes in the instrument (including scoring procedure) may impact study results.
Instrumentation Threat
55
Characteristics of data gatherers can influence study outcomes.
Data Collector Characteristics
56
Data collectors or scorers may unconsciously distort the collected data.
Data Collector Bias
57
Use of a pre-test may create a "practice effect" influencing study results or participant responses to an intervention.
Testing Threat
58
Unforeseen or unplanned events during the study may impact the results.
History Threat
59
Changes during an intervention may be due to the passing of time rather than the intervention itself.
Maturation Threat
60
The way subjects view a study, and their participation is a threat to internal validity.
Subject Attitude
61
participants change their behaviours when they are aware of their role as research subjects.
John Henry and Hawthorne effect
62
The experimental group may be treated in unintended ways, giving them an undue advantage, and affecting the results.
Implementation Threat
63
Caused by selecting subjects based on extreme scores or characteristics, leading to potential distortions in the results.
Regression Threat
64
a faulty data collection method can lead to gathering of incorrect and invalid data.
Inability to Answer Research Questions
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With manipulated and biassed data from the project, other researchers may find it difficult to get the same data or result, despite following the same procedure for each method used in the study.
Effect on the Repeatability and Validity of Research
66
Data derived from faulty data collection tend to distort the truth regarding the research question being addressed in the project.
Distorted Findings
67
Once distorted data collected through a faulty procedure is published, other researchers who will read this research may be misled.
Misleading Other Researchers
68
Policies that will be formulated based on faulty and distorted data will be highly compromised.
Compromising Decisions for Public Policy
69
may refer to the activities that can be done before data collection begins.
Quality assurance
70
includes the activities that must be done during and after data collection.
Quality control
71
deals with the collection, organization, analysis of data and drawing of inferences from the samples to the population.
Statistics
72
Any information that has been collected, observed, generated or created to validate original research findings.
Data
73
A variable is an essential component of any statistical data. It is unique, and can differ in quantity or quality from another member of the same sample or population.
Variable
74
Classifies data into categories in which no order or ranking can be imposed on the data.
Nominal
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Categories can be ranked, though precise differences between each ranking can't be determined.
Ordinal
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Data can be ranked with precise differences in between, but there is no meaningful zero.
Interval
76
Possesses the same characteristics of interval level but with the existence of a true zero.
Ratio
77
Laerd Statistics (2018) mentions the ambiguities in classification of variables in which "in some cases, the measurement scale for data is ordinal, but the variable is treated as continuous."
Ambiguities in Classification of Variables
78
Try to describe the variables in a sample or population. It consists of the collection, organization, summarization, and presentation of data.
Descriptive Statistics
79
Use a random sample of data taken from a population to describe and make inferences about the whole population.
Inferential Statistics
80
also known as the arithmetic mean
sum of all scores divided by the number of scores.
Mean
81
can be defined as a research process that involves repeated observations of the same groups of people, whether that's employees, a specific group of customers, or another audience group to see if their opinions have changed since you first collected their data.
Longitudinal Survey
82
a type of research design in which you collect data from many different individuals at a single point in time
cross-sectional survey
83
the middle of a distribution in a ranked data
Median
84
the most frequently occurring variable in a distribution
Mode
85
a measure of how spread out is the distribution.
Variance
86
Square root of variance.
Standard Deviation
87
The highest value minus the lowest value.
Range
88
Gaussian distribution
described as a continuous, bell-shaped, distribution of a variable
Normal Distribution
89
is a decision-making process for evaluating claims about a population.
Hypothesis Testing
90
is a tentative statement about the relationship between variables.
Hypothesis
91
denotes that there is no relationship (difference) between the population variables in question.
Null Hypothesis
92
denotes that there is a relationship (difference) between the population variables in question.
Alternative Hypothesis
93
a value calculated from a statistical test which describes the probability of obtaining the observed results, assuming that the null hypothesis is true.
P-Value
93
P-Value: scientific and medicine-related
0.01%
94
P-value: educational research
0.05%
95
P-value: Other studies
0.10%
96
Rejecting the null hypothesis when it is true.
Type I Error
97
Occurs if you do not reject the null hypothesis when it is false.
Type II Error
98
A distribution that is asymmetrical because the data values trail off more sharply on one side than on the other.
Skew Distribution
99
It is measure of the asymmetry of distribution
Skewness
100
Less than -1 or greater than +1, the distribution
highly skewed
101
Between -1 or -0.5 or between +0.5 and +1
moderately skewed
102
-0.5 between +0.5
skewed approximately
103
It measures the thickness of the tails and the center of the distribution
Kurtosis
104
Type of Kurtosis: <0 (negative)
Platykurtic (N)
105
Type of Kurtosis: 0 (or close to 0)
+/- 0.01 - +/- 0.09
Mesokurtic (0)
106
Type of Kurtosis: >0 (positive)
Leptokurtic (N)
106
Most commonly used type of statistical analysis. This analysis is referred to as parametric statistical analysis because the findings are inferred to the parameters of normally distributed populations
Parametric Test
107
Both test for normality
P-value > 0.05
Kolmogorov-Smirnov Test and Shapiro-Wilks Test
108
The assumption of normality which specifies that the means of the sample group are normally distributed.
Assumptions
109
Test for equal variances
Levene's Test
110
Parametric Test: Used to compare a sample mean to a specific value.
One sample T-test
111
Parametric Test: Can be used when the two groups under comparison are independent of each other.
Unpaired or Independent T-test
111
Parametric Test: Can be used when the two groups under comparison are dependent on each other.
Paired or Dependent T-test
112
Parametric Test: Used to determine one or more factors and their interactions differed significantly from that expected by chance.
One-way ANOVA
113
Parametric Test: One-way ANOVA; Unequal Variances
Welch’s Test
114
Parametric Test: One-way ANOVA; Equal Variances
Fisher's Test
115
Types of Post-hoc test (parametric)
Bonferonn’s
Tukey’s
Scheffe’s
116
Parametric Test: To examine both the separate and the combined effects of the variables on the same measure of behavior.
Two-way ANOVA
117
Parametric Test: Association between two groups; Assesses the linear relationship between two variables.
Pearson Correlation Coefficient
118
statistical analysis or distribution free techniques
It can be used in studies that do not meet the first two assumptions
Non-parametric Test
119
Non-parametric test: one sample
Wilcoxon Signed Rank’s Test
120
Non-parametric test: two sample; Dependent
Non-parametric counterpart of the paired t-test.
Wilcoxon Signed Rank’s Test
120
Non-parametric test: two sample; Used to compare differences between two independent groups when the dependent variable is.
Mann-Whitney U Test
121
Non-parametric test: three or more sample; One factor
This test determines whether three or more independent samples belong to the same population based on medians.
Kruskal-Wallis H Test
122
Non-parametric test; Association between Two Groups
Spearman’s Rank Order of Correlation
122
123
Type of Post-hoc test under Kruskal-wallis
Dunn test,
Conover test,
Nemenyi test
Dwass–Steel–Critchlow–Fligner test
124
Non-parametric test: three or more sample; two factor Rank-based, non-parametric test for several related samples
Friedman Test
