Correlational research
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Correlational research investigates potential relationships between variables without manipulating them. Researchers seek associations between variables to help explain behaviors or predict outcomes. If a strong enough relationship exists between two variables, scores on one can be used to predict the other. Correlational techniques include multiple regression, coefficient of multiple correlation, and factor analysis. Researchers must consider threats to internal validity like subject characteristics, instrumentation, and data collector bias.
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Introduction
In life, there are universal laws that govern everything we do. These laws are so perfect that if you were to align yourself with them, you could have so much prosperity that it would be coming out of your ears. This is because God created the universe in the image and likeness of him. It is failure to follow the universal laws that causes one to fail. The laws that were created consisted of the following: ·
Law of Gratitude: The Law of Gratitude states that you must show gratitude for what you have. By having gratitude, you speed your growth and success faster than you normally would. This is because if you appreciate the things you have, even if they are small things, you are open to receiving more.
Law of Attraction: The Law of Attraction states that if you focus your attention on something long enough you will get it. It all starts in the mind. You think of something and when you think of it, you manifest that in your life. This could be a mental picture of a check or actual cash, but you think about it with an image.
Law of Karma: the Law of Karma states that if you go out and do something bad, it will come back to you with something bad. If you do well for others, good things happen to you. The principle here is to know you can create good or bad through your actions. There will always be an effect no matter what.
Law of Love: the Law of Love states that love is more than emotion or feeling; it is energy. It has substance and can be felt. Love is also considered acceptance of oneself or others. This means that no matter what you do in life if you do not approach or leave the situation out of love, it won't work.
Law of Allowing: The Law of Allowing states that for us to get what we want, we must be receptive to it. We can't merely say to the Universe that we want something if we don't allow ourselves to receive it. This will defeat our purpose for wanting it in the first place.
Law of Vibration: the Law of Vibration states that if you wish on something and use your thoughts to visualize it, you are halfway there to get it. To complete the cycle you must use the Law of Vibration to feel part of what you want. Do this and you'll have anything you want in life.
For everything to function properly there has to be structure. Without structure, our world, or universe, would be in utter chaos. Successful people understand universal laws and apply them daily. They may not acknowledge that to you, but they do follow the laws. There is a higher power and this higher power controls the universe and what we get out of it. People who know this, but wish to direct their own lives, follow the reasons. Successful people don't sit around and say "I'll try," they say yes and act on it.
Chapter - 1
The Law of Attraction
The law of attraction is the most powerful force in the universe. If you work against it, it can only bring you pain and misery. Successful people know this but have kept it hidden from the lower class for centuries because th
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Causal-comparative research attempts to identify potential cause-and-effect relationships by comparing two or more groups that differ on some independent variable. Researchers select naturally occurring groups that vary on the independent variable, rather than manipulating the variable through experimentation. There are three types: exploration of effects, causes, and consequences. Threats to internal validity include lack of randomization and control. Analysis involves comparing means and frequencies between groups using t-tests, ANCOVA, or other inferential statistics.
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This document summarizes key aspects of experimental design and methods for coding texts from media research. It discusses the components of experimental design including causality, theory, control, and ecological validity. It also outlines different types of intentionalities to analyze in media texts, such as those of the author, text, audience, and interpreter. Finally, it provides guidance on coding texts by establishing the texts of interest, analytical approach, unit of analysis, coding scheme, and analysis.
Brm unit iv - cheet sheet
This document discusses various topics related to data preparation and analysis, including editing, coding, data entry, validity of data, qualitative vs quantitative analysis, bivariate and multivariate statistical techniques like multiple regression, factor analysis, discriminant analysis, cluster analysis, multidimensional scaling, and the application of statistical software like SAS, SPSS, and R. It provides an overview of key concepts and steps involved in preparing data for analysis and using different statistical methods to analyze the relationships between variables.
تلخيص انواع الابحاث.pdf
The document summarizes different types of research including quantitative, qualitative, and mixed methods research. It provides details on non-experimental and experimental quantitative research designs, as well as survey research, correlation research, causal comparative research, and secondary data research. Descriptions of true experimental, pre-experimental, and quasi-experimental designs are also given. The summary highlights key aspects of research methodology discussed in the document.
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2012-Nathans-PARE-RegressionGuidebook.pdf
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The Elaboration ModelIntroductionThe elaboration mod.docx
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·IntroductionQuantitative research methodology uses a dedu.docx
·
Introduction
Quantitative research methodology uses a deductive reasoning process (Erford, 2015, p. 5). It is based on philosophical assumptions that are very different from those that support qualitative research. Quantitative studies fall under what is broadly described as a positivist perspective. Epistemologically, knowledge is something that is believed to be objective and measurable, and the nature of reality (that is, ontology) is such that there is one fixed, observable, and definable reality. Quantitative approaches to research emphasize the objectivity of the researcher, and because a goal is to uncover the one true reality, values (axiological assumptions) and the subjective nature of experience are not likely to be examined.
Quantitative Research Designs
Quantitative research can be categorized in different ways. Brief descriptions of some designs appear below. The chosen research design is determined by the nature of the inquiry, that is, what the researcher wants to learn by conducting the study.
Counseling Research: Quantitative, Qualitative, and Mixed Methods
thoroughly describes several major reseach.
Experimental Research
Experimental research, one of the quantitative designs, involves random selection and random assignment of subjects to two or more groups over which the researcher has control. This is what distinguishes experimental studies from the other designs. Experimental studies in counseling are not that common, because many research questions do not lend themselves to random selection and assignment for ethical reasons. Experimental studies compare the effect of one or more independent variables on one or more dependent variables. Independent variables fall into two broad categories. One type of independent variable involves measuring some characteristic inherent in the study's participants, such as their age, gender, IQ, personality traits, income, or education level. These demographic or blocking variables are not something which the researcher can manipulate, though the researcher can statistically control for them. The treatment or experimental conditions that the researcher sets up is the other type of independent variable, which is unique to experimental designs. The element of control is what permits researchers to conclude that one variable has caused a change in another variable.
Quasi-Experimental Research
Quasi-experimental research designs come in many different forms. Like experimental research, the researcher aims to compare the effect of the independent variable under their control on the dependent variable. However, the researcher does not or cannot randomly assign individual participants to treatment and control groups, so cause-and-effect relationships cannot be as strongly inferred from the results. Pre-existing conditions of one group in comparison to the other may confound the findings. An example might be a study to examine the potential effects of a new curriculum aimed at reducin.
Causal comparative research
Causal-comparative research attempts to identify cause-and-effect relationships by comparing two or more groups that differ on some independent variable. It is a nonexperimental method used to explore potential causes of existing differences between groups. Researchers select groups that already differ on the independent variable rather than manipulating the variable. Common threats to validity include lack of randomization and inability to control for confounding variables. Analysis typically involves comparing means and using t-tests or ANOVAs to determine if differences between groups are statistically significant.
2 types of research
The document discusses different types of research:
- Exploratory research is flexible and informal, used to gain background on a problem. It does not provide conclusive evidence but informs subsequent research.
- Descriptive research describes characteristics but not causes. Cross-sectional studies measure variables at one time; longitudinal studies do so over time.
- Correlational research determines the relationship between variables but cannot indicate causation. The correlation coefficient measures strength and direction of relationships.
- Explanatory research aims to understand relationships between independent and dependent variables to explain phenomena rather than just report them. It tests and advances theoretical explanations.
Lec 2 types of research
The document discusses different types of research:
- Exploratory research is flexible and informal, used to gain background on a problem. It does not provide conclusive evidence but informs subsequent research.
- Descriptive research describes characteristics but not causes. It can profile populations through cross-sectional or longitudinal studies.
- Correlational research determines the relationship between variables but cannot prove causation. The correlation coefficient indicates the strength and direction of relationships.
- Explanatory research aims to understand relationships between independent and dependent variables to explain phenomena rather than just report observations. It tests and advances theoretical explanations.
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This document discusses research problems and types of educational research. It begins by defining a research problem as an area of concern, condition to be improved, or troubling question that requires investigation. The purpose of a research problem is to introduce importance, place the problem in context, and provide a framework for reporting results.
The document then discusses three main types of educational research: historical research which investigates past events; descriptive research which describes current conditions without manipulation; and experimental research which manipulates and examines the effects of variables. Descriptive research includes field studies, ex-post-facto research, survey research, content analysis, and case studies. Key aspects and limitations of each type are outlined. Criteria for a good
Business Research Methods, Ch. 19New Message · Chapter 19 C.docx
Business Research Methods, Ch. 19
New Message
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Chapter 19: Cluster Analysis The thread has 1 unread message.
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Message collapsed. Message unread Chapter 19: Cluster Analysis
posted by Jynx Gresser at Mar 07, 2015, 11:34 PM
Last updated Mar 07, 2015, 11:34 PM
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According to Cooper and Schindler (2011), cluster analysis is "a set of interdependence techniques for grouping similar objects or people" (p. 550). This method is often utilized in the fields of medicine, biology, and marketing (Cooper & Schindler, 2011). Within the field of marketing, one can divide customers into groups based on buying behaviors as well as age, lifestyle, and financial characteristics (Cooper & Schindler, 2011). Cluster analysis is often compared to a factor analysis, but differs in the ways that correlations are treated; they are similarity measures rather than control variables on a linear model (Cooper & Schindler, 2011). There are five basic steps in the application of cluster analysis and they include selection of the sample to be clustered, definition of the variables on which to measure objects, events, or people, computation of similarities through correlations, selection of mutually exclusive clusters, and cluster comparison and validation (Cooper & Schindler, 2011). The biggest takeaway from this analysis method is clustering similar groups together to provide a heightened awareness of links between data amongst different demographic variables. A dendogram provides a visual representation on how to categorize clusters and understand their differences. I look forward to utilizing this type of analysis when I begin my marketing classes that involves product development and how it effects buying behavior. Does anyone in class utilize this method and have some insight into how it is applied?
Reference
Cooper, D. R., & Schindler, P. S. (2011). Business Research Methods (11th ed.). New York, NY: McGraw's/Irwin. Retrieved from the University of Phoenix eBook Collection database.
Jynx Gresser
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SEM The thread has 3 unread messages.
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Structural equation modeling (SEM) implies a structure for the covariances between observed variables, and accordingly it is sometimes called covariance structure modeling. More commonly, researchers refer to structural equation models as LISREL (linear structural relations) models--the name of the first and most widely cited SEM computer program.
SEM is a powerful alternative to other multivariate techniques, which are limited to representing only a single relationship between the dependent and independent variables. The major advantages of SEM are (1) that multiple and interrelated de ...
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- 1. CORRELATIONAL RESEARCH Reported by: Aileen Mae B. Romero Kristine C. Soltis
- 2. Researchers investigate possible relationships among variables without trying to influence those variables. I. The Nature of Correlational Research a. The major characteristic of correlational research is seeking out associations among variables. II. Purposes of Correlational Research a. Correlational studies are carried out either to help explain important human behaviors or to predict likely outcomes.
- 3. b. If a relationship of sufficient magnitude between two variables, it becomes possible to predict a score on either variable if a score on the other variable is known. III. Complex Correlational techniques a. Multiple regressions b. The coefficient of multiple correlations (R) c. The value of a prediction equation d. When the criterion variable
- 4. e. Factor analysis f. Path analysis IV. Basic Steps in Correlational Research a. Problem Selection b. Sample c. Instruments d. Design and Procedures e. Data Collection f. Data Analysis and Interpretation
- 5. V. What do Correlation coefficients tell us? a. The meaning of a given correlation coefficient depends on how it is applied. VI. Threats to internal validity in Correlational Research a. Subject Characteristics b. Location c. Instrumentation d. Data-collector Characteristics
- 6. e. Data-collector Bias f. Testing g. Mortality VII. Evaluating Threats to Internal Validity in Correlational Studies a. Ask: What are the specific factors that are known to affect one of the variables being correlated or which logically would affect it? b. Ask: What is the likelihood of each of these factors also affecting the other variable being correlated with the first?
- 7. c. Evaluate the various threats. VIII. An Example of Correlational Research Chapter Objectives Reading this chapter should enable students to: Describe briefly what is meant by association research; State the two major purposes of correlational studies; Distinguish between predictor and criterion variables;
- 8. Explain the role of correlational studies in exploring causation; Explain how a scatterplot can be used to predict an outcome; Describe what is meant by a prediction equation; Explain briefly the main ideas underlying multiple correlation, factors analysis, and path analysis; Identify and describe briefly the steps involved in conducting a correlational study;
- 9. Interpret correlation coefficients of the different magnitude; Explain the rationale underlying partial correlation; Describe some of the threats to internal validity that exist in correlation studies, and explain how to identify them; Discuss how to control for these threats; Recognize a correlational study when they come across one in the educational research literature. Points to Stress Teaching Suggestion and Class Activities
- 10. The End ! The End !