LU Active & Attribute Independent Variables Discussion Responses

Please respond to the 4 disccusion responses below:

1) Laura Corvino

D1.1.Compare the terms active independent variable and attribute independent variable. What are the similarities and differences?

A particular characteristic referring to a situation or to certain participants in a study can be called a variable and can assume different values (Morgan et al. 2013).  The independent variable can be also called the active variable and can be manipulated in different ways depending on the scope of the study. The dependent variable will manifest different characteristics and/or results based on the independent variable. The dependent variable depends on the independent variable and its reaction in the study will be observed by the scientists in order to determine the outcomes of the research (Morgan et al. 2013). The research is conducted to observe the causal relationship between the dependent and independent variables. The input data is operated on the independent variable, while the dependent variable will respond in a certain way by confirming (or dis-confirming) causation and providing information about the correlation between the two.

D1.2.What kind of independent variable (active or attribute) is necessary to infer cause? Can one always infer cause from this type of independent variable? If so, why? If not, when can one infer cause and when might causal inferences be more questionable?

There are two different kinds of independent variables: active and attribute. The causal relationship between these two variables is the main focus and what will be investigated during the study. The independent variable will be studied to determine if the changes in the dependent variables have been caused directly by the independent variable. When the independent variables present are too many can be difficult or even impossible to infer correctly the causation to the correct active independent variable. In fact, only the active independent variable can confirm that the change in the dependent was caused by the independent variable. An attribute independent variable has characteristics that do not change during the study, instead, the active independent variable will be manipulated and controlled to eventually cause the expected changes. It is not possible to always infer causation with any kind of independent variable because there are secondary factors that cannot be always controlled that can determine the outcome of the experiments and eliminate direct causation. Sometimes is difficult if not impossible to attribute the cause of change to one specific variable.

D1.3.What is the difference between the independent variable and the dependent variable?

The simplest and most direct way to explain such a difference is to consider cause and effect. The independent variable is the cause, while the dependent variable is the effect. So the scientists will produce a hypothesis and then they will test it by manipulating the independent variable (called also input in mathematics) and by observing the reactions in the dependent variable (also called output) they will determine the conclusion of the study and confirm or reject the original hypothesis (Spanos, 2019).

D1.4.Compare and contrast association, difference, and descriptive types of research questions.

Research questions can be an associational, focused on differences, and descriptive. Associational research questions, as their name suggests, analyze the kind of relationship or association between two variables. They examine the relationship between the variations in the independent and dependent variables. They examine the degree of change that the independent variable infers over the dependent variable.

The difference research question focuses on investigating the different outcomes produced in two or more different groups of individuals or subjects. These kinds of research questions observe the differences in outcomes when the independent variables act in the presence of different circumstances. This kind of research is comparative and uses a control group to determine if an independent variable is affecting a group in the presence of other variables.

The Descriptive research questions simply collect data through surveys and describe and explain a determined event without testing causation, or differences. They just state and describe what is going on.  

D1.5.Write a research question and a corresponding hypothesis regarding variables of interest to you but not in the HSB datasets. Is it an associational, difference, or descriptive question?  

Research (Associational) Question: “Can low and consistent intakes of Cayenne Pepper help in losing weight?”

Hypothesis: “Consistently taking low quantities of Cayenne Pepper can speed up the basic metabolism and help in losing weight”

This is an associational question that investigates the existence of causation between taking Cayenne pepper in low dosages and losing weight. The hypothesis is positive suggesting that Cayenne pepper will cause a loss of weight. The hypothesis will be tested to be confirmed, rejected, or determined that the study was inconclusive (Morgan et al. 2013).

D1.6. Using one or more of the following HSB variables, religion, mosaic pattern test, and visualization score

(a.)Write an associational question.

(b.)Write a difference question.

(c.)Write a descriptive question.

Is there a relationship of causation between the religious affiliation of an individual and their propensity to have a successful marriage?

How the propensity to have a successful marriage change among different religious groups? (Jewish vs Christians Vs Muslims vs Buddhists, for example)

How the different religious groups perceive marriage. Is it viewed as an important sacrament to respect and honor or it is not particularly important in that particular faith? These considerations that may lead to a conclusion between the two variables (being affiliated with a religious group and having a successful marriage) explain, investigate, and discuss the relationship between the two.

2) Eduardo Sanguino

D1.1: Compare the terms active independent variable and attribute independent variable. What are the similarities and differences?

An active independent variable refers to an element introduced during a study, specifically targeted at a group of participants within a specified time frame. These variables hinge on interactions initiated by a source other than the researcher, with examples including interventions like workshops or new curricula (Morgan et al., 2020). To ensure validity, it is essential to provide an opportunity for a pretest, thus necessitating that these treatments be administered after the study has been meticulously planned (Morgan et al., 2020). In contrast, attribute independent variables are inherent and unaltered by the study or the participant’s surrounding environment, whether intentionally or unintentionally. These attributes are unique to each individual and remain constant even when similarities exist. Common examples of attribute independent variables encompass age, IQ, or socioeconomic status. The study primarily centers on these attribute independent variables (Morgan et al., 2020).

D1.2: What kind of independent variable (active or attribute) is necessary to infer cause?

According to Morgan et al. (2020), causality is established by employing an active independent variable to collect data that substantiates any alterations or variances in a dependent variable. This statement underscores yet another contrast between the two categories of independent variables, with “active” suggesting change and “attributive” highlighting stability.

D1.2.a: Can one always infer cause from this type of independent variable? If so, why? If not, when can one infer cause, and when might causal inferences be more questionable?

A researcher cannot always deduce causation when dealing with an active variable, as not all aspects are amenable to change. Non-experimental studies involving attribute independent variables can, however, shed light on associations between variables and differences among group members, although these findings often imply correlation rather than establishing causation (Morgan et al., 2020).

D1.3: What is the difference between the independent variable and the dependent variable?

The dependent variable depends on an independent variable for a measurable or assessable impact. According to Morgan et al. (2020), the dependent variable is characterized as a “presumed outcome or criterion” with a minimum of two values, often spanning a range from low to high. For instance, a dependent variable might involve measuring blood pressure, which could have three values: increase, decrease, or remain stable. In this scenario, the independent variable would be the treatment factor, with multiple levels that may be associated with or responsible for each value observed in the dependent variable.

D1.4: Compare and contrast associational, difference, and descriptive types of research questions.

Researchers employ three types of research questions to clarify their objectives. Associational questions aim to uncover relationships between two or more factors and an additional variable, enabling the formulation of predictions. Difference questions, on the other hand, focus on a specific dependent variable and highlight the distinctions between two or more groups. Descriptive questions, in contrast to the previous two types, do not require inferential statistics for answers. Their purpose is to depict data by quantifying the variables of interest in the study (Morgan et al., 2020).

D1.5: Write a research question and a corresponding hypothesis regarding variables of interest to you but not in the HSB dataset. Is it an associational, difference, or descriptive question?

What is the relationship between micro-credentials and salary and benefits on job satisfaction between managers and non-managers? This is an associational research question. A hypothesis for this question suggests that if the administration supports non-managers in obtaining micro-credentials, it may lead to salary increases, thus subsequently enhancing job satisfaction.

D1.6: Using one or more of the following HSB variables, religion, mosaic pattern test, and visualization score:

D1.6.a: Write an association question.

Does a negative relationship exist between a student’s mathematics achievement and their performance?

1. D1.6.b Write a difference question.
2. Do disparities in math achievement exist between students whose fathers have higher levels of education and students whose mothers have higher levels of education?
3. D1.6.c Write a descriptive question.

What percentage of high school students who study trigonometry achieve high scores in math?

3) Ryan Haun

D1.1.a. Active Independent Variables

            An active independent variable is a variable that the researcher intentionally manipulates or controls in an experiment. It is also known as a manipulated independent variable because it is altered by the researcher to observe its impact on the dependent variable. The purpose of manipulating an active independent variable is to determine whether changes in this variable lead to changes in the dependent variable (Morgan et al., 2020).

D1.1.b. Attribute Independent Variable

            An attribute independent variable is a variable that is not manipulated by the researcher but is observed or measured as it naturally exists. It is also known as a subject or participant variable because it describes inherent characteristics or attributes of the research participants. Attribute independent variables include factors like age, gender, race, socioeconomic status, personality traits, or pre-existing conditions that are not under the researcher’s control (Morgan et al., 2020).

D1.1.c. Similarities and Differences

           Both types of independent variables play parts in experimental research by influencing the observed outcomes. Both active and attribute independent variables can have an impact on the dependent variable. Researchers examine these relationships to understand how changes in the independent variable(s) affect the outcome (Morgan et al., 2020).

           Researchers have control over active independent variables, and they intentionally manipulate or vary them during an experiment. This manipulation allows for testing cause-and-effect relationships. Attribute independent variables are inherent characteristics of research participants, and researchers do not manipulate them. They are observed or measured as they naturally exist. Active independent variables are typically used in experimental research designs, where researchers actively intervene and change the variable to assess its effects on the dependent variable. Attribute independent variables are often used in observational or non-experimental research, where the researcher observes and measures existing attributes of participants. These variables are not directly manipulated in such studies (Morgan et al., 2020).

D1.2 Inferring Cause

           To infer cause-and-effect relationships, an active independent variable is necessary. Active independent variables can be manipulated by researchers in experiments. Manipulation is a fundamental aspect of experimental design for establishing causality. Exercising control allows researchers to isolate the impact of the independent variable on the dependent variable. In experimental research, researchers create different conditions or treatment groups to test the effects of the active independent variable. By comparing these groups, they can draw conclusions about whether changes in the independent variable caused changes in the dependent variable. In experimental research, researchers typically formulate hypotheses that predict the specific effects of the active independent variable on the dependent variable. By manipulating the independent variable and comparing the outcomes to their hypotheses, they can test whether the independent variable is a cause of the observed effects (Morgan et al., 2020). The use of an active independent variable in experimental research can enhance the ability to establish cause-and-effect relationships, but it does not guarantee that causation can always be inferred. The quality of the experimental design is important and should include controls over the independent variable (Morgan et al., 2020).

D1.3 Independent and Dependent Variables

           The independent variable is intentionally manipulated in an experiment. It is the presumed cause being tested to determine its effect on another variable. Researchers manipulate the independent variable to observe how it can lead to changes in the dependent variable. It can be manipulated to test hypotheses and establish cause-and-effect relationships (Morgan et al., 2020).

           The dependent variable is the variable that the researcher measures or observes to assess the effect of changes in the independent variable. The dependent variable is expected to change because of variations in the independent variable. The data obtained are used to draw conclusions about the impact of the independent variable (Morgan et al., 2020).

D1.4 Research Questions

           Associational research questions aim to understand the relationships between two or more variables. They investigate whether there is a statistical association, correlation, or link between variables and explore the extent that changes in one variable could be associated with changes in another without implying causation.

           Difference research questions aim to identify differences between groups, conditions, or time periods and investigate whether there are statistically significant distinctions between them. The purpose is to assess the magnitude and significance of differences and can involve hypothesis testing to determine if there are meaningful distinctions.

           Descriptive research questions aim to describe, summarize, or characterize a particular phenomenon, group, or situation. They provide a detailed account of the subject under investigation. These questions do not typically involve testing hypotheses or making comparisons; instead, they focus on providing an accurate and comprehensive portrayal of the subject.

D1.4.a. Compare and Contrast

           Associational research questions explore associations or correlations between variables without implying causation. Difference research questions focus on identifying significant variations between groups or conditions. Associational research questions explore relationships between variables. Descriptive research questions focus on providing a detailed description of a phenomenon. Associational questions investigate links or associations, while descriptive questions aim to present an overview. Associational questions may involve correlation or regression analysis, while descriptive questions may involve summary statistics and content analysis. Difference research questions compare groups or conditions. Descriptive research questions provide a detailed account without making comparisons. Difference questions seek distinctions, while descriptive questions aim to describe without comparing. Difference questions often involve hypothesis testing, while descriptive questions primarily involve summarizing and reporting data.

D1.5 Research Question and Hypothesis

           Research question: Does alcohol consumption by pregnant women affect the prevalence of fetal developmental delay? This is a difference research question because it seeks to determine causation.

           Hypothesis: Pregnant women who consume increasing amounts of alcohol will experience progressively higher levels of fetal developmental delay.

D1.6 Using HSB Variables

D1.6.a.

           Associational question: Is there a correlation between academic track and high school grades?

D1.6.b.

           Difference question: Is there a significant difference in students’ math achievement test scores between those whose parents are college educated and those whose parents are not?

D1.6.c.                                            

           Descriptive question: What are the ethnic characteristics and religions of students in the academic fast track?

4) Rita De La Fuente

D1.1 Compare the term active independent variable and attribute independent. What are the similarities and differences?

D1.1 The term active independent variable can be manipulated and changed by the researcher. Active independent variables are necessary but insufficient to make an effective conclusion (Morgan et al., 2020). On the contrary, the term attribute independent variable cannot be manipulated or changed, and it is a significant study factor (Morgan et al., 2020). Both active independent variables and attribute independent variables are independent variables. They are the cause and are independent of other study variables (Morgan et al., 2020).

D1.2 What kind of independent variable (active and attribute) is necessary to infer cause? Can one always infer cause from this type of independent variable? If so, why? If not, when can one infer cause and when might causal inference be more questionable?

D1.2 According to Morgan et al. (2020) both active and attribute independent variables can be utilized to infer cause on a study. It is essential to distinguish the term main effect and effect size between the active and attribute independent variables to be able to analyze properly (Morgan et al., 2020). The study must demonstrate the interpretation to have an accurate outcome.

D1.3 What is the difference between the independent variables and dependent variables?

D1.3 The difference between independent variables and dependent variables is dependent variables measure the effect of the independent variable, and the independent variable is the variable that controls or changes the study (Morgan et al., 2020).

D1.4 Compare and contrast associational, difference, and descriptive types of research questions.

D1.4 While associational, difference, and descriptive are all research questions, the three have different purposes. Associational research questions relate to two or more groups and determine how they work together (Morgan et al., 2020). Difference research questions compare two or more different groups and attempt to demonstrate that the groups are not the same (Morgan et al., 2020). The study does not answer Descriptive research questions; instead, they are the data summary of the study (Morgan et al., 2020).

D1.5 Write a research question and a corresponding hypothesis regarding variables of interest to you but not in the HSB dataset. Is it an associational, difference, or descriptive question?

D1.5 Descriptive Research Question: What is the percentage of college students away from home who feel depressed? Hypothesis: More parent visitations from college students away from home may result in a lower rate of depressed students.

D1.6 Using one or more of the following HSB variables, religion, mosaic pattern test, and visualization score:

Write an associational question.

Write a difference question. 

Write a descriptive question.

D1.6.a Is there a high percentage of moral standards in students, whether they are protestant, catholic, or non-religious?

D1.6.b Which religion protestant, or catholic, have a higher moral standard in students?

D1.6.c What percentage of students belong to a religion?