# Beginning cholesterol level

Response Post

1) Specify two hypotheses in which one variable is the independent variable in one hypothesis and the dependent variable in the other. Don’t just reverse the variables (making the dependent variable the independent variable and vice versa). ONE variable should be the independent variable in one hypothesis and the dependent variable in the other hypothesis. Operationally define the independent variable and dependent variable in both hypotheses. Try to hypothesize one positive relationship and one negative relationship.

One issue that has most recently came up is the calling for the defunding of police. Many people are questioning what that model would look like and I feel this is a good opportunity to try and see if we can develop a snapshot of what that could look like.

Hypothesis one:

The defunding of police would create an increase of funds available for social services.

Hypothesis two:

The defunding of police would decrease the amount of police brutality.

2) Explain the difference between mediating and moderating variables. Come up with yet another hypothesis that includes: independent variable, dependent variable, mediating variable, and moderating variable.

Moderating variables are that give affect the relationship of the dependent variable while mediating variables are more of causal chain that effects the independents variables (Rubin & Babbie 2017).

Hypothesis:

Defunding the police would lead to an increase mental health treatment available in impoverished communities

3) Explain what a spurious causal relationship is and come up with an example. Explain what the extraneous variable is that made the relationship between the independent variable and the dependent variable spurious. Finally, explain the difference between an extraneous variable and a control variable.

a spurious casual relationship occurs when a third controlled variable is introduced and it destroys the relationship between the independent variable and the dependent variables (rubin & babbie 2017). An example of this would be that defunding the police results in an increase of certain crimes that are caused by mental health and addictions issues. The extraneous relationship occurred when the fact that crimes can be committed due to someone’s addiction or mental health issues, how do we enforce the law and treat addiction.

Rubin, A. & Babbie, E. (2017). Research Methods for Social Work (9th ed). Independence, KY: Cengage.

1) Specify two hypotheses in which one variable is the independent variable in one hypothesis and the dependent variable in the other. Don’t just reverse the variables (making the dependent variable the independent variable and vice versa). ONE variable should be the independent variable in one hypothesis and the dependent variable in the other hypothesis. Operationally define the independent variable and dependent variable in both hypotheses. Try to hypothesize one positive relationship and one negative relationship.

Hypothesis 1: Consuming diet soda will increase blood sugar levels

IV: Diet Soda

DV: Blood Sugar Levels

Hypothesis 2: Teenagers (ages 13-18) consume the most diet soda.

IV: Study samples of age groups (Ex: Teenagers 13-18yo, Adults 19-23yo, Older Adults 30-35yo)

DV: Diet Soda

Rubin & Babbie (2017, p. 172) explain that operationally defining a variable refers to translating variables into observable terms, or what we use to determine the quantity or attribute of a particular variable.

In Hypothesis 1, the independent variable of diet soda is operationally defined by the type of drink and how the manufacturer labels it. The scale of blood sugar testing can operationally define the dependent variable. The positive relationship between the two variables is likely that an increase in drinking diet soda will likely increase blood sugar levels.

In Hypothesis 2, the independent variable of the age of the study groups can be operationally defined by the indirect observation (self-report survey) of the participants in the study. The type of drink and manufacturer label would once again be the determining attribute of the dependent variable. The negative relationship would be to find that teenagers drink less diet soda than another age group in the study.

2) Explain the difference between mediating and moderating variables. Come up with yet another hypothesis that includes: independent variable, dependent variable, mediating variable, and moderating variable.

According to Rubin & Babbie (2017, p. 170), a mediating variable affects the relationship between the independent and dependent variables as it acts as a medium that occurs between the stages and moves something from the stage of the independent variable to the stage of the dependent variable. Also know as intervening variables, mediating variables are found in the middle of the causal chain between the independent and dependent variables. As explained by Dr. Radey (2020), the mediating variable acts as a mechanism for change and explains why or how the independent variable causes change in the dependent variable.

In contrast, Rubin & Babbie (2017, p. 170) define a moderating variable as one that resides outside the causal chain between the independent variable and the dependent variable but can influence the degree of relationship between the two variables.

Example hypothesis ( I realize I have used a simple example, but it was the only way for me to wrap my head around this concept, although I’m not confident I have):

Eating pizza will lead to higher cholesterol levels.

IV = Pizza

DV= cholesterol levels

Mediating Variable: Type of pizza. Is it low-calorie pizza with a cauliflower crust and vegetables as toppings, or is it a deep-dish pizza with pepperoni and bacon topping?

Moderating Variable: Beginning cholesterol level

3) Explain what a spurious causal relationship is and come up with an example. Explain what the extraneous variable is that made the relationship between the independent variable and the dependent variable spurious. Finally, explain the difference between an extraneous variable and a control variable.

A spurious causal relationship between the independent and dependent variables is one that disappears when a third variable is controlled, and the connection no longer exists (Rubin & Babbie, 2017, p. 168). An example of a spurious relationship is when sales of Christmas decorations increase, so do the number of snow-related sports accidents. The extraneous third variable is the season, winter, and there is no direct link between the purchase of Christmas decorations and snow sports accidents.

While an extraneous variable shows alternative explanations for connections observed between independent and dependent variables, a control variable is an extraneous variable that can be controlled for in the design of the study (Rubin & Babbie, 2017, pp. 167-168).

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