This document discusses correlational research design. It defines correlational research as a procedure that measures subjects' scores on two variables without manipulating any variables to determine if a relationship exists. The document outlines key aspects of correlational research, including types (explanatory and predictive), characteristics, tools used, procedures, and interpreting strength of correlation. It provides examples and discusses how correlation is calculated using Excel or SPSS.
The phi coefficient is that system of correlation which is computed between two variables, where neither of them is available in a continuous measures and both of them are expressed in the form of natural or genuine dichotomies. This presentation slides describes the concept and procedures to do the computation of phi coefficient of correlation.
The phi coefficient is that system of correlation which is computed between two variables, where neither of them is available in a continuous measures and both of them are expressed in the form of natural or genuine dichotomies. This presentation slides describes the concept and procedures to do the computation of phi coefficient of correlation.
Correlation & Regression Analysis using SPSSParag Shah
Concept of Correlation, Simple Linear Regression & Multiple Linear Regression and its analysis using SPSS. How it check the validity of assumptions in Regression
Pearson Product Moment Correlation - ThiyaguThiyagu K
The coefficient of correlation computed by product moment coefficient of correlation or Pearson's correlation coefficient and symbolically represented by r. This presentation explains the concept, computation, merits and demerits of Pearson Product Moment Correlation.
Topic: What is Reliability and its Types?
Student Name: Kanwal Naz
Class: B.Ed 1.5
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
Validity:
Validity refers to how well a test measures what it is purported to measure.
Types of Validity:
1. Logic valididty:
Validity which is in the form of theory, statements. It has 2 types.
I. Face Validity:
It is the extent to which the measurement method appears “on its face” to measure the construct of interest.
• Example:
• suppose you were taking an instrument reportedly measuring your attractiveness, but the questions were asking you to identify the correctly spelled word in each list
II. Content Validity:
Measuring all the aspects contributing to the variable of the interest.
Example:
For physical fitness temperature, height and stamina are supposed to be assess then a test of fitness must include content about temperatures, height and stamina.
2. Criterion
It is the extent to which people’s scores are correlated with other variables or criteria that reflect the same construct
Example:
An IQ test should correlate positively with school performance.
An occupational aptitude test should correlate positively with work performance.
Types of Criterion Validity
Concurrent validity:
• When the criterion is something that is happening or being assessed at the same time as the construct of interest, it is called concurrent validity.
• Example:
Beef test.
Predictive validity:
• A new measure of self-esteem should correlate positively with an old established measure. When the criterion is something that will happen or be assessed in the future, this is called predictive validity.
• Example:
GAT, SAT
Other types of validity
Internal Validity:
It is basically the extent to which a study is free from flaws and that any differences in a measurement are due to an independent variable and nothing else
External Validity
• It is the extent to which the results of a research study can be generalized to different situations, different groups of people, different settings, different conditions, etc.
Overviews non-parametric and parametric approaches to (bivariate) linear correlation. See also: http://en.wikiversity.org/wiki/Survey_research_and_design_in_psychology/Lectures/Correlation
Correlation & Regression Analysis using SPSSParag Shah
Concept of Correlation, Simple Linear Regression & Multiple Linear Regression and its analysis using SPSS. How it check the validity of assumptions in Regression
Pearson Product Moment Correlation - ThiyaguThiyagu K
The coefficient of correlation computed by product moment coefficient of correlation or Pearson's correlation coefficient and symbolically represented by r. This presentation explains the concept, computation, merits and demerits of Pearson Product Moment Correlation.
Topic: What is Reliability and its Types?
Student Name: Kanwal Naz
Class: B.Ed 1.5
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
Validity:
Validity refers to how well a test measures what it is purported to measure.
Types of Validity:
1. Logic valididty:
Validity which is in the form of theory, statements. It has 2 types.
I. Face Validity:
It is the extent to which the measurement method appears “on its face” to measure the construct of interest.
• Example:
• suppose you were taking an instrument reportedly measuring your attractiveness, but the questions were asking you to identify the correctly spelled word in each list
II. Content Validity:
Measuring all the aspects contributing to the variable of the interest.
Example:
For physical fitness temperature, height and stamina are supposed to be assess then a test of fitness must include content about temperatures, height and stamina.
2. Criterion
It is the extent to which people’s scores are correlated with other variables or criteria that reflect the same construct
Example:
An IQ test should correlate positively with school performance.
An occupational aptitude test should correlate positively with work performance.
Types of Criterion Validity
Concurrent validity:
• When the criterion is something that is happening or being assessed at the same time as the construct of interest, it is called concurrent validity.
• Example:
Beef test.
Predictive validity:
• A new measure of self-esteem should correlate positively with an old established measure. When the criterion is something that will happen or be assessed in the future, this is called predictive validity.
• Example:
GAT, SAT
Other types of validity
Internal Validity:
It is basically the extent to which a study is free from flaws and that any differences in a measurement are due to an independent variable and nothing else
External Validity
• It is the extent to which the results of a research study can be generalized to different situations, different groups of people, different settings, different conditions, etc.
Overviews non-parametric and parametric approaches to (bivariate) linear correlation. See also: http://en.wikiversity.org/wiki/Survey_research_and_design_in_psychology/Lectures/Correlation
Research methods can generally be divided into two main categories: Quantitative and Qualitative. This webinar will provide an overview of quantitative methods with a brief distinction between quantitative and qualitative methods. We will focus on when and how to use quantitative research and discuss type of variables and statistical analysis.
Presentation will be led by Dr. Carlos Cardillo.
About CORE:
The Culture of Research and Education (C.O.R.E.) webinar series is spearheaded by Dr. Bernice B. Rumala, CORE Chair & Program Director of the Ph.D. in Health Sciences program in collaboration with leaders and faculty across all academic programs.
This innovative and wide-ranging series is designed to provide continuing education, skills-building techniques, and tools for academic and professional development. These sessions will provide a unique chance to build your professional development toolkit through presentations, discussions, and workshops with Trident’s world-class faculty.
For further information about CORE or to present, you may contact Dr. Bernice B. Rumala at Bernice.rumala@trident.edu
How to choose the right statistics techniques in different situation. This short presentation provide a compact summary on various method of statistics either descriptive and inferential.
for further inquiry please reach me at bodhiyawijaya@gmail.com
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
4. Topics to Be Discussed
What is research design?
Design vs. method.
Correlation research
Types of correlation research.
Key characteristics of correlation research.
Steps or procedure of conducting
correlation research
How to evaluate the correlation research.
4
5. What is research design?
To under stand what is research design an
analogue may help us.
When constructing a building there is no point ordering materials or
setting critical dates for completion of project stages until we know
what sort of building is being constructed.
whether we need a high rise of building, a factory for manufacturing
Machinery, a school, a residential home or an apartment block.
Until this is done we cannot sketch a plan, obtain permits, and work
out a work Schedule or order materials.
Similarly, social research needs a design or a structure before data
Collection or analysis can commence.
5
6. What is research design?
The function of A research design is to ensure that the evidence
obtained enables us to answer the Initial-How do we evaluate a
Correlational Study all question as unambiguously as possible.
In other words, when designing research we need to ask: given this
research question (or theory), what type of evidence is needed to
answer the question (or test the theory) in a convincing way?
Research design `deals with a logical problem and not a logistical
problem' (Yin, 1989: 29).
6
7. Design vs. method
How the data are collected is irrelevant to the logic of the Research
design is different from the method by which data are collected.
. There are many research methods that provide a loose framework
or guidelines to conduct a research project. One has to choose a
method that suits the requirements of the project and the
researcher is comfortable with.
On the other hand, research design is the specific framework within
which a project is pursued and completed. Many remain confused
about the differences between research methods and research
design.
Research design refers to the blue print that you prepare using the
research method chosen and it delineates the steps that you need
to take.
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8. Design vs. method
Research design tells how the goals of a research project can be
accomplished.
Key features of any research design are methodology, collection and
assignment of samples, collection and analysis of data along with
procedures and instruments to be used.
8
9. Correlation research
A procedure in which subjects’ scores on two variables are simply
measured, without manipulation of any variables, to determine
whether there is a relationship
Correlational research examines the relationship between two or
more non manipulated variables.
Involves collecting data or searching out records of a specified
population and ascertaining the relationships among the variables of
interest.
The correlational approach is sometimes referred to as the study of
individual differences because emphasis is placed on differences
among individuals.
9
10. Correlation Research
What is the relationship between:
Height and weight?
Birth order and years of education?
Cigarettes smoked per day and health care costs?
How close to the front you sit in a classroom and your grade in a
class?
Can high school grades be used to predict college grades.
Does physical exercise cause people to lose weight.
To examine the possible existence of causation.
10
11. What can correlational research tell us?
Imagine that researchers find an
association between sitting in the front of
the classroom and receiving good grades
You promptly move to the front of the
classroom, and expect your grade will
improve
11
12. Correlation Research
Operational Definition:
A statistical analysis of covariant data to determine a pre-existing
relationship. Researcher makes no attempt to manipulate an
independent variable.
Purpose:
This research technique is used to relate two or more variables and
allow predictions of outcomes based on causative relationships
between the variables.
12
13. Correlation Research
Historical Perspective:
Karl Pearson introduced modern correlation techniques in 1895
at a Royal Society meeting in London where he illustrated his
statistical model using Darwin’s evolution and Galton’s heredity.
Improvements were slow coming until the arrival of
microcomputers when complex regressional analysis of multiple
variables was possible
13
14. Correlation Research
Example Situation:
We, as teachers, practice correlation research often
in the forms of pre-tests, quizzes, dip-sticking, etc.,
where we correlate (based on years of experience) the
outcome of these assessments with anticipated final test
results. We will often modify our teaching in response to
the data to modify the outcome.
14
15. Types of correlational design
Explanatory Design:
Research looks for simple associations between
variables and investigates the extent to which the
variables are related
Prediction Design:
Research designed to identify variables that will
positively predict outcomes
15
16. Types of correlational design
Key Characteristics of ERD
Correlation of two or more variables
Data collected at one time
Single group
At least two scores recorded
Correlation Statistical Test- Strength and Direction of
correlation determined
Researcher draws conclusions from statistics alone
16
17. Types of correlational design
Key Characteristics of PRD
Author states that prediction
capability is the goal of the research
Use of predictor variable followed
with a criterion variable
Author forecasts future performance
17
18. Characteristics of Correlational
Design
As suggested by the explanatory &
prediction design, Correlation research
includes specific characteristics:
Displays of scores
Associations between scores (direction,
form, & strength)
Multiple variable analysis (partial
correlation & multiple regression)
18
21. Procedure of correlation research
variable to be selected are identified
Question and /or hypothesis are stated .
A sample is selected ( a minimum of 30 is needed)
Data are collected
Correlations are calculated.
Results are reported.
For each individual in the research , there must be at least two
measures , or it will be impossible to calculate a correlation.
A correlation is reported as “ r “ such as r =.36
The statistical probability is reported as “ p”.
21
22. Procedure of correlation
research
Some researchers report the probability as of the correlation
happening by chance was P .05 ( More than 5 out of 100) or
P< .05 ( Less than 5 out of 100)
Other researcher report the actual probability ; P = .03
The first approach was used before the age of computers.
Either approach is acceptable.
Correlation can be range from = 1.00 to 1.00
A 1.00 is a perfect positive correlation .
As one variable increases , so does the other.
- 1.00 is a perfect negative correlation .
- As one variable increases, the other variables decreases.
22
23. Procedure of correlation
research
A -00 correlation indicates no correlation
Means there is no relationship between one variable and another.
23
24. Interpretation of the strength of correlation
.00 to .20 very weak
0.21 to .40 weak
.41 to .60 Moderate
.61 to .80 Strong
.81 to 1.00 Very strong
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26. How to calculate correlation
Excel has a statistical function . It calculates pearson product
moment correlation.
SPSS calculates correltion.
26