the negative linear relationship statistics homework help

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Writing that needs a response is below

Linear (regression line, or best fit) is a relationship between two variables on the scatterplot, which creates a straight line when graphed on a Pearson correlation coefficient (r). The linear relation could have a “positive value of r .54 or r .67″ (p.163) or negative linear “negative value of r -3 or r .-72″ (Stangor, 2013, p.163). The linear appears as slope in a graphical format, then, use statistical techniques by researchers in aim to explain the relation between a variable and a constant. We can describe a positive linear when the line of best fit has a straight line going towards the top right corner of the graph, with above- average values on one variable have the same tend with above-average values on the other variable. However, a negative linear is when above- average values of one variable tend, to associate with below-average values on the other variable. Therefore, the straight line the negative linear go towards down right corner of the graph (Stangor, 2013).

However, the non-linear relation is a relationship between two or more variables that does not create a straight line due to a typical pattern (or independent). And because of that, when it is graphed on a Pearson correlation coefficient (r) the researcher cannot use one variable to predict the other. Otherwise, the patterns of association are not well described by a single straight linear. In this situation; the data run at a lower point (a negative direction), which means a negative decline. Additionally, curvilinear relationship occurs when there is little or no relation between the X and Y values, which means the relationship is likely to be about zero (Stangor, 2013).

Compared to linear and non-linear relationships, in my opinion, student can use first the linear relationship in the research for being easier to work on, and easy to understand. However, if there was a difficulty in having the best fit with linear relation, then the researcher can move to the nonlinear regression. In the non-linear relationship is little complicated, as the student might not be able to model the exact curve linear that occurs in hisher data.

Below are two articles that focus on Domestic Violent cases:

First article: Intimate partner violence and incidence of type 2 diabetes in women.

With interest in this study; Mason, et al. (2013), wanted to evaluate three areas about partners. Looking for answers with evidence about if there were a relation between intimate partner violence (IPV), a prevalent psychosocial stressor, and the incidence of type 2 diabetes in women. According to the authors’ and after reviewing the extant literature relates to the same matters; they found that the recent research had shown that child abuse and IPV are in risk situations and may influence type 2 diabetes. The researchers explained that type 2 diabetes could happen from depression due to the emotional reactions that could lead to insulin resistance. As a result, experts developed this study with the aim to control this risk by examining the relationship between IPV experienced in adulthood and the occurrence of type 2 diabetes in women from age eighteen-year-old and above in the longitudinal Nurses’ Health Study II (NHSII).

The research design was a questionnaire related to experiences of interpersonal violence through their lifetime, and the contributors sourced from NHSII. The survey examined three significant IPV exposures: a) physical IPV, b) sexual IPV, and c) inti­mate relationship IPV in 2001. The participants’ total number was 91,297 and responses’ umber was 68,376 (75 percent). The two variables that have a positive linear relationship were found as follow

1. 15–20% increases in type 2 diabetes incidences associated with physical IPV in adulthood, and
2. WEB (Women’s Experiences with Battering) score used as measured for recent severe psychological IPV, which associated with an almost 80% increased risk of type 2 diabetes. Which both of them show a strong positive association. (Mason, et al., 2013)

But the negative linear relationship found in the increases in risk associated with adult sexual IPV even there were of similar magnitude (10 percent), but were not statistically significant, which shows a weak association. As well, negative linear relationship or no relationship (curvilinear relationship) found of adult IPV variables and child abuse. Due to no statistical evidence for interactions between age and abuse. In this case, I could name it a lack of association (r approximately 0) (Mason, et al., 2013).

In the second article, “Factors influencing domestic and marital violence against women in Ghana.” Were Tenkorang, Owusu, Yeboah and Bannerman (2013) purposed to examine and explore the relationships between both physical, sexual abuse and the marriage women in Ghana. To observe and understand the patterns of this case, authors used new updated Ghana Demographic, Health Survey, and “employing complementary log-log models” (p. 4). The researchers created three models to present each for physical and sexual abuse, purposing each one to examine variables of the effects of community economic variables, scores cultural variables; and life course and family violence variables.

There was negative linear relationship between both wealth and employment status, and sexual abuse has weak relation, as the study showed by percentage a 5.1among married woman in Ghana. As well, control variables were with low associated with sexual assault in married women in rural compared to urban areas. The positive linear relationship found in life course variables, which showed a high relates to both physical and sexual abuse among married women in Ghana. For example:

1. Positive correlation between the controlled women from their husbands, with a greater chance of experiencing physical and sexual violence. And this happened due to drinking alcohol with 60 % and 85 %, which is 2.5 times and 2.9 times more likely to experience physical and sexual violence respectively, due to cultural variables.
2. As well between lower education and physical violence among Ghanaian women, as it was the very strong relation by 18.4 percent, higher compared to the sexual abuse for the same group of age (32 years old was the average age of the women in this sample study, same rural areas, same religion).
3. Another positive relation that best fit, is ladies who witness their fathers beat their wives were in a high chance to experience higher levels of physical and sexual abuse, were about 69 % and 2.7 times more likely to have experienced both physical and sexual abuse.

References

Borum, R., Cornell, D. G., Modzeleski, W., & Jimerson, S. R. (2010). What can be done about school shootings? A review of the evidence. Educational Researcher, 39(1), 27-37.

Mason, S. M., Wright, R. J., Hibert, E. N., Spiegelman, D., Jun, H. J., Hu, F. B., & Rich-Edwards, J. W. (2013). Intimate partner violence and incidence of type 2 diabetes in women. Diabetes care, 36(5), 1159-1165.

Moore, L., & Finn, P. E. (1986). Forensic psychology: An empirical review of experimental research. Journal of Clinical Psychology, 42(4), 675–679.
National Institute of Justice. (2008). Measuring recidivism. Retrieved from http://www.nij.gov/topics/corrections/recidivism/m…

National Center for the Analysis of Violent Crime. (n.d.). Investigative programs: Critical incident response group. Retrieved October 1, 2009, from http://www.fbi.gov/about-us/cirg/investigations-an…

Stangor, C. (2013). Research methods for the behavioral sciences (Laureate Education, Inc., custom ed.). Boston: Houghton Mifflin Company. (PP.160-180)

Tenkorang, E. Y., Owusu, A. Y., Yeboah, E. H., & Bannerman, R. (2013). Factors influencing domestic and marital violence against women in Ghana. Journal of family violence, 28(8), 771-781.

 

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