PR 2 Q1

Qualitative Research

a research method that focuses on understanding the 'why' and 'how' of social phenomena. It delves into experiences, perspectives, and meanings rather than numerical data.

Quantitative Research

Based on the use of computational procedures; objective and methodical investigation of recognizable phenomena.

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Non experimental

Describe a situation or phenomenon

Positive correlation

An increase to one variable leads to increase the other variable, vice versa

Negative correlation

An increase in one variable, decrease to other one, vice versa

No correlation

A change in one variable is may not necessarily see to the other one

Quantitative Research

Emphasizes numerical analysis of data.

Quantitative Research

Implications: aims for precision, reproducibility, and generalizability of findings.

Descriptive Research

Aims to describe the characteristics of a population or phenomenon being studied.

Descriptive Research

Can be both qualitative (e.g., describing experiences) and quantitative (e.g., describing frequencies).

Descriptive Research

Focuses on 'what is' rather than 'why' or 'how'.

Experimental Research

Often includes control groups and random assignment

Experimental Research

Involves manipulating one or more independent variables to observe their effect on a dependent variable

Experimental Research

Primarily quantitative, it aims to determine cause-and-effect relationships between variables.

Historical Research

Can inform present decisions by understanding past patterns

Historical Research

Uses primary and secondary sources to reconstruct or interpret a historical narrative.

Historical Research

Systematic collection and evaluation of data to describe, explain, and understand past events.

Qualitative Approach

Aims to explore an idea or phenomenon without measuring it, focusing on understanding perspectives, experiences, and meanings (as described above).

Quantitative Approach

Aims to test hypotheses or theories by measuring variables and analyzing numerical data, often using statistical methods.

Correlational Design

Examines the relationship between two or more variables without assuming a cause-and-effect relationship.

Causal Design

Aims to establish a cause-and-effect relationship between variables.

Experimental Design

Typically involves manipulating an independent variable and observing its impact on a dependent variable under controlled conditions.

Research Abstract

‎A brief, comprehensive summary of a research study or paper.

Purpose of Research Abstract

Provides an overview of the research, allowing readers to quickly grasp its essence without reading the entire paper.

Content of Research Abstract

Typically includes the research question or objectives, methodology (design, participants, data collection), key findings, and main conclusions or implications.

Characteristics of Research Abstract

Concise, self-contained, and typically ranges from 150 to 300 words, depending on the journal or publication guidelines.

Dependent Variables (DV)

: The variable being measured or tested in an experiment. It 'depends' on the independent variable.

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Independent Variables (IV)

: The variable that is changed or controlled in a scientific experiment to test the effects on the dependent variable.

Variables

symbols to express numerical data

Confounding Variable

Extraneous variables that are related to both the independent and dependent variables, potentially distorting the true relationship between them.

Intervening Variable

Hypothetical variables that explain a causal link between other variables (e.g., stress leading to poor health, with 'coping style' as an intervening variable).

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Control Variable

Variables that are kept constant or accounted for in a research study to prevent them from influencing the relationship between the independent and dependent variables

Nominal Variable

Categorical data where there is no inherent order or ranking (e.g., gender, type of car).

Interval Variable

Numerical data where the order and exact differences between values are meaningful, but there is no true zero point (e.g., temperature in Celsius or Fahrenheit).

Ordinal Variable

Categorical data with a meaningful order or ranking, but the intervals between categories are not necessarily equal (e.g., socio-economic status: low, medium, high).

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Continuous Variable

Can take any value within a given range, including decimals or fractions (e.g., time, precise measurements)

Discrete variable

Numerical data that can only take specific, distinct values and cannot be meaningfully divided (e.g., number of children, number of cars).

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Ratio variable

Numerical data with a meaningful order, exact differences, and a true zero point, allowing for meaningful ratios (e.g., height, weight, income).

Ratio variable

Can’t be negative or zero

Discrete variable

Countable limited numbers

Interval Variable

Can measure negative datas

Continuous variable

Measuring limitless data

Nominal variable

cannot be ordered in any way

Ordinal variable

Can be ordered

Confounding variable

Influence cannot be detected directly

Control variable

Affects the result, must be hold during experiment

Correlational

Describe and measure the association between 2 or more variable or sets of scores

Descriptive

Describing Chrscteristics

Experimental

Manipulates condition and study effects

Discrete

Number of kids

Continuous

Miles

Continuous

Kilogram

Interval

Temperature

Ratio

IQ test

Interval

Time

Ratio

Height and weight

Ordinal

Liked the scale

Nominal

Hair , eye color

Ordinal

Socio economic status

Nominal

Religion