Res Flashcards
(47 cards)
Researchers aim to maintain a
neutral stance , minimizing bias
Objectivity
- Information is collected in
numerical form, such as numbers , percentages
,and statistic
Numerical data
Involves a significant
number of participants to ensure representativeness
Large sample sizes
Data collected using standardized tools like
questionnaires, surveys, or experiments
Structured Research Instruments
Findings can often be applied
to larger populations beyond the study sample.
Generalizability
- Involves formulating and
testing hypotheses
Hypothesis Testing
Clearly defined variables are used to measure and quantify
phenomena
Measurable Variables
Research can be replicated to verify results due to standardized methods
Reliability
Data is analyzed using statistical methods to identify patterns and relationships
Statistical Analysis
Quantitative research can be used to predict future trends or outcomes
Predictive
A factor or property that a researcher measures,
controls and/or manipulates. It is also a logical set of
attributes, characteristics, numbers, or quantities that
can be measured or counted.
VARIABLES
It is also called a DATA ITEM
VARIABLES
7 Types of Classifications of Variables
Numerical Variables, Continuous Variables, Discrete Variables, Categorical Variables, Ordinal Variables, Nominal Variables, Dichotomous Variables
2 types of Continuous Variables
Interval Variables, Ratio Variables
- Can be measured numerically.
- Answer the questions “how many” or how much”
Numerical Variables
These variables can take on any value within a specific range, often represented by decimals.
Continuous Variables
are also called interval variables
Continuous Variables
These variables have equal
intervals between values, but there is no true zero
point.
Interval Variables
are a special type of continuous
variable.
Ratio Variables
These variables have equal intervals between values and a true zero point, allowing for meaningful
ratios
Ratio Variables
These variables can only take on specific, whole
number values.
Discrete Variables
Variables with values that describe a quality or characteristic of data like “what type” or “which
category”
Categorical Variables
These variables can take a value which can be logically
ordered.
Ordinal Variables
These variables whose values cannot be ranked.
Nominal Variables