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HMPYC 80 - Research Methodology Summary Notes - Chapter 9 CA$8.07   Add to cart

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HMPYC 80 - Research Methodology Summary Notes - Chapter 9

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Excellent quality study notes for the Honours module, HMPYC 80. This document contains study notes for Chapter 09 in Research at Grass Roots (5th edition). Perfect for tests, assignments and/or exams. The notes are in English and were summarised in 2021 using the textbook and the 2021 tutorial lett...

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  • August 31, 2021
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HMPYC 80:
Research
Methodology

Chapter 09 –
Quantitative Research
Designs HMPYC 8

, ➢ 1. Defining Research Design:
• Research design refers to a specific set of predetermined guidelines, steps and formulas in a kind of template
according to which quantitative researchers can design a research project that suits their specific research pu


➢ 2. Types of Quantitative Research Designs:
• Campbell and Stanley, as well as Cook and Campbell, provide us with well-structured classifications in the h
services professions.
- Based on this, quantitative research designs are categorised according to the level of scientific rigour invo
proving cause-and-effect relationships, which range from pre-experimental to quasi-experimental to true e
designs.

• Leedy & Ormrod also add ex post facto (Lat. “after the fact”) designs and factorial designs.

• A similar classification is made by Grinnel & Unrau who distinguish between non-experimental, quasi-expe
experimental research designs.

• Punch categorises quantitative designs on a continuum, where the true experiment is at the left-most end
experimental (correlational surveys) at the right-most end and the quasi-experiment in the middle.

• When we discuss quantitative designs, we follow a notational system proposed by Cook & Campbell.
- Traditionally, in this notational system, X stands for a treatment or independent variable where the study
experimental and the X is manipulated on purpose.

, ➢ 2. Types of Quantitative Research Designs:
• Alternatively, we can also regard X as a natural event or phenomenon in a study where X is still independent
those who observe, but is not under our control and happens spontaneously.
- O stands for an observation and the way we study a group of participants or unit of analysis (P) in relation t
variable (X).

• In experimental studies the subscripts 1 through n (𝑥1 … 𝑥𝑛 ) refer to the sequential order of implementing tr
recording observations (𝑂1 … 𝑂𝑛) [ a dotted line between experimental groups indicates that they were not
formed.]

• Generally, we use scales in quantitative studies to measure how participants respond to the Xs of the study.
- This implies that the measures should always reflect the X of the study.
- The data obtained from observations of our participants are the dependent variables.

• In the notational system, we distinguish between U- and C-studies as follows:
1. U-studies are more exploratory and descriptive in nature. They require the use of simple descriptive statistic
aim to seek support for a hypothesis, or statistical testing. These studies help us understand situations bette
qualitative studies and descriptive quantitative studies never reach beyond the understanding level. Non-ra
purposive sampling (NR) is frequently the choice in qualitative or U-studies.
2. C-studies aim to compare groups or examine relationships between variables by means of some form of sta
hypothesis testing. Random sampling (R) is the preferred sampling technique in most quantitative studies.

, ➢ 2. Types of Quantitative Research Designs:
• Notational system for depicting quantitative research designs:

X The independent variables that influence participants

P The group of “people” (participants) we observe

O The way we observe the relationship between X and P

R Random assignment of participants to a group

NR Non-random assignment of participants to a group

E Experimental group of participants

C Control group of participants

U-Study “Understanding” type of study (hypothesis generating, exploratory/descriptive)

C-Study Confirmation type of study (explain phenomena by means of a hypothesis)

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