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Practical research 2, Study notes of Earth science

Earth science

About practical research, quarter 1

Typology: Study notes

2022/2023

Uploaded on 09/30/2024

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faith-hernandez-1 🇵🇭

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QUANTITATIVE RESEARCH uses scientifically collected and statistically analyzed data to investigate
observable phenomena.
Strengths of Quantitative Research
The following are the strengths of quantitative research.
1. Quantitative research can be replicated or repeated.
2. Findings are generalizable to the population.
3. Conclusive establishment of cause and effect
4. Numerical and quantifiable data can be used to predict outcomes
5. Fast and easy data analysis using statistical software.
6. Fast and easy data gathering
7. Very objective
8. Validity and reliability can be established
Weaknesses of Quantitative Research
The following are the disadvantages of quantitative research:
1. It lacks the necessary data to explore a problem or concept in depth.
2. It does not provide a comprehensive explanation of human experiences.
3. Some information cannot be described by numerical data such as feelings, and beliefs.
4. The research design is rigid and not very flexible.
5. The participants are limited to choose only from the given responses.
6. The respondents may tend to provide inaccurate responses.
7. A Large sample size makes data collection more costly.
Characteristics of Quantitative Research
Quantitative research is commonly used in natural sciences research problems because of the
following characteristics:
1. To obtain more meaningful statistical result, the data must come from a large sample size.
2. OBJECTIVE. Data gathering and analysis of results are done accurately, objectively, and are unaffected
by the researcher’s intuition and personal guesses.
3. VISUAL RESULT PRESENTATION. Data is numerical, which makes presentation through graphs, charts,
and tables possible and for better conveyance and interpretation.
4FASTER DATA ANALYSIS. The use of a statistical tools give way for a less time-consuming data analysis.
5. GENERALIZED DATA. Data taken from a sample can be applied to the population if sampling is done
accordingly, i.e., sufficient size and random samples were taken.
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QUANTITATIVE RESEARCH uses scientifically collected and statistically analyzed data to investigate observable phenomena. Strengths of Quantitative Research The following are the strengths of quantitative research.

  1. Quantitative research can be replicated or repeated.
  2. Findings are generalizable to the population.
  3. Conclusive establishment of cause and effect
  4. Numerical and quantifiable data can be used to predict outcomes
  5. Fast and easy data analysis using statistical software.
  6. Fast and easy data gathering
  7. Very objective
  8. Validity and reliability can be established Weaknesses of Quantitative Research The following are the disadvantages of quantitative research:
  9. It lacks the necessary data to explore a problem or concept in depth.
  10. It does not provide a comprehensive explanation of human experiences.
  11. Some information cannot be described by numerical data such as feelings, and beliefs.
  12. The research design is rigid and not very flexible.
  13. The participants are limited to choose only from the given responses.
  14. The respondents may tend to provide inaccurate responses.
  15. A Large sample size makes data collection more costly. Characteristics of Quantitative Research Quantitative research is commonly used in natural sciences research problems because of the following characteristics:

1. To obtain more meaningful statistical result, the data must come from a large sample size.

  1. OBJECTIVE. Data gathering and analysis of results are done accurately, objectively, and are unaffected by the researcher’s intuition and personal guesses.
  2. VISUAL RESULT PRESENTATION. Data is numerical, which makes presentation through graphs, charts, and tables possible and for better conveyance and interpretation. 4 FASTER DATA ANALYSIS. The use of a statistical tools give way for a less time-consuming data analysis.
  3. GENERALIZED DATA. Data taken from a sample can be applied to the population if sampling is done accordingly, i.e., sufficient size and random samples were taken.
  1. FAST DATA COLLECTION. Depending on the type of data needed, collection can be quick and easy. Quantitative research uses standardized research instruments that allow the researcher to collect data from a large sample size efficiently. For instance, a single survey form can be administered simultaneously to collect various measurable characteristics like age, gender, socio-economic status, etc.
  2. RELIABLE DATA. Data is taken and analyzed objectively from a sample as a representative of the population,
  3. REPLICATION. The Quantitative method can be repeated to verify findings enhancing its validity, free from false or immature conclusions. KINDS OF QUANTITATIVE RESEARCH DESIGN Descriptive design is used to describe a particular phenomenon by observing it as it occurs in nature. There is no experimental manipulation and the researcher does not start with a hypothesis. THE CORRELATIONAL DESIGN IDENTIFIES THE RELATIONSHIP BETWEEN VARIABLES. DATA IS COLLECTED BY OBSERVATION SINCE IT DOES NOT CONSIDER THE CAUSE AND EFFECT FOR EXAMPLE, THE RELATIONSHIP BETWEEN THE AMOUNT OF PHYSICAL ACTIVITY DONE AND STUDENT ACADEMIC ACHIEVEMENT EX POST FACTO DESIGN IS USED TO INVESTIGATE A POSSIBLE RELATIONSHIP BETWEEN PREVIOUS EVENTS AND PRESENT CONDITIONS. THE TERM “ EX POST FACTO ”, MEANS AFTER THE FACT, LOOKS AT THE POSSIBLE CAUSES OF AN ALREADY OCCURRING PHENOMENON. A QUASI-EXPERIMENTAL DESIGN IS USED TO ESTABLISH THE CAUSE AND EFFECT RELATIONSHIP OF VARIABLES. ALTHOUGH IT RESEMBLES THE EXPERIMENTAL DESIGN, THE QUASI-EXPERIMENTAL HAS LESSER VALIDITY DUE TO THE ABSENCE OF RANDOM SELECTION AND ASSIGNMENT OF SUBJECTS. HERE, THE INDEPENDENT VARIABLE IS IDENTIFIED BUT NOT MANIPULATED. EXAMPLE, THE EFFECTS OF UNEMPLOYMENT ON ATTITUDE TOWARDS FOLLOWING SAFETY PROTOCOL IN ECQ DECLARED AREAS. EXPERIMENTAL DESIGN LIKE QUASI- EXPERIMENTAL IS USED TO ESTABLISH THE CAUSE AND EFFECT RELATIONSHIP OF TWO OR MORE VARIABLES. THIS DESIGN PROVIDES A MORE CONCLUSIVE RESULT BECAUSE IT USES RANDOM ASSIGNMENT OF SUBJECTS AND EXPERIMENTAL MANIPULATIONS. FOR EXAMPLE, A COMPARISON OF THE EFFECTS OF VARIOUS BLENDED LEARNING TO THE READING COMPREHENSION OF ELEMENTARY PUPILS. A VARIABLE IS ANYTHING THAT HAS A QUANTITY OR QUALITY THAT VARIES INDEPENDENT VARIABLE IS THE MANIPULATES OR CHANGES , AND IS ASSUMED TO HAVE A DIRECT EFFECT ON THE OTHER VARIABLE. DEPENDENT VARIABLE THESE VARIABLES ARE EXPECTED TO CHANGE AS A RESULT OF AN EXPERIMENTAL MANIPULATION. SINCE EXTRANEOUS VARIABLES MAY AFFECT THE RESULT OF THE EXPERIMENT, IT IS CRUCIAL FOR THE RESEARCHER TO IDENTIFY THEM PRIOR TO CONDUCTING THE EXPERIMENT AND CONTROL THEM IN SUCH A WAY THAT THEY DO NOT THREATEN THE INTERNAL VALIDITY OF THE RESULT. EXTRANEOUS VARIABLE IS ANY VARIABLE THAT YOU'RE NOT INVESTIGATING THAT CAN POTENTIALLY AFFECT THE DEPENDENT VARIABLE OF YOUR RESEARCH STUDY..

CONFOUNDING VARIABLES ARE THOSE THAT AFFECT OTHER VARIABLES IN A WAY THAT

PRODUCES SPURIOUS OR DISTORTED ASSOCIATIONS BETWEEN TWO VARIABLE.