What Are The Statistics Of Gender And Racial Differences In Advertising

Statistics provides us with very useful tools and techniques that aide us in dealing with real world scenarios. I have been able to learn several useful concepts by studying statistics that can aide me in making rational and informed decisions that are supported by the analysis results. Statistics as a discipline is the application and development of various processes put in place to gather, interpret, and analyse the information. The quantification of biological, social, and scientific phenomenons, design and analysis of experiments and surveys, and application of

Research focusing on the calculation of racial disparities in police outcomes has generally examined police traffic stops and the follow up police activities, such as, citations, search and warnings. Review of these studies suggests that calculation methods of racial disparity vary from one study to another; however, majority of those studies employed population as a baseline measure or benchmarking variable (Withrow, 2002; Smith & Petrocelli, 2001; Withrow & Williams, 2015). Early studies using population as a baseline measure to compare disproportionate traffic stop counts found substantial racial disparities (Lamberth, 1996; Verniero & Zoubek, 1999). Studies later have begun to discuss that

Race and gender are two important terms in society that define us. However, they lead to inequality among individuals. "Race is a socially defined category based on real or perceived biological differences between groups of people" (Ferris and Stein 216). It is based off our biological makeup that distinct us from others (Ferris and Stein). Many people do not know the actual term of race, how deeply rooted it is, or where it derived from, but it all works in one form. Race goes a long way from how you may appear to someone. Just because someone looks a certain race does not mean they will not have inevitably biological material from other races. It is very diverse between many different populations. Race does not identify who you are but what social category you are from. Gender is how you physically appear in society. "Gender is the physical, behavior, and personality traits that a group considers to be normal, natural, right, and good for its male and female members" (Ferris and Stein 243). It is the identity of masculine and feminine. Gender identifies who we are and it reflects deeply on a person's personality. They normally change over time from the assigned sex given at birth. Society has its way of discriminating between race and gender and it shows differences distributed among individuals.

Prior to this course I have used statistics in my professional life. During my previous employment at the University of Tennessee, College of Veterinary Medicine I worked in the student admissions which made my primary job focus the student application process. This process required me to compile statistical information on our applicant pool for faculty and administrative staff to determine who would be accepted. This statistical data included both categorical data, such as current grade level in undergraduate studies, gender, and ethnicity, as well as numerical data such as age, GPAs, average number of courses taken in a semester, credit hours completed, and test scores (Mirabella, 2011). After the admissions process was completed, these different

Statistics, facts, data, and comparisons are absorbing and challenging to present in a way that is anything other than, well, boring. For purposes of an informational presentation, the statistics are unavoidable. However, in this

I believe that gender codes in advertising do have an effect on how we interact with people as we picture how people are ‘supposed to look’ from advertising and compare them to the people we see in our day to day lives. When we see people who are acting different than the media dictates they should act then we silently judge them and maybe whisper about how they should be acting according to what we see on the media. It is especially explicit when we look at female athletes as they are powerful and strong in their sport but the media has them pose in accordance of the gender codes for women, so that people can see that they are truly feminine and not too masculine, since they play sports. As well for some sports how we dress to play the sports also follows gender codes where we should be wearing skimpy clothes that are revealing, this is explicit in volleyball where girls wear spandex that barely covers and a tight shirt to go along with it, and it is seen as weird if girls wear anything other than that to play. As well gender codes dictate what professions certain genders should have so when I see certain people in professions the opposite gender typically is in it could appear as weird to people since they only see males being plumbers, electricians, or mechanics, and females as nurses, maids, and stay at home moms.

Measuring racial and ethnic equality is not a simple or straightforward task. As Gary M. Klass points out in the “Measuring Racial and Ethnic Inequality” chapter of his book Just Plain Data Analysis:Finding, Presenting, and Interpreting Social Science Data, “Numbers never speak for themselves.” Klass’s purpose for this chapter is to demonstrate the range of data that is derived from social indicators that can be used to analyze racial and ethnic disparities in different spheres such as income and wealth, health, education, and criminal justice. After summarizing the chapter, Klass’s methodology and findings can be discussed and evaluated.

Dating back to the 1800’s, racism and gender inequality have played a prominent role in America. Ranging from slavery to the Jim Crow laws to the war on drugs, racial inequality is present in our everyday lives. Likewise, gender inequality is also as prominent as there are many inherent barriers for women in the workplace such as sexual harassment, inability to ascend into high ranking jobs and stereotypes involving gender roles. Even with the implementation of anti-discrimination laws, racial and gender inequality would still be present in our society because many disparities between race and gender are not caused by explicit discrimination but rather implicit discrimination. Anti-discrimination laws promote equality in theory, but not so much in practice as legal reasoning isn’t exempt from ethical or political beliefs.

Current statistics show that men commit 80% of all crime and women commit only 20%. However there are arguments to suggest that the statistics highlight an under representation of female criminality, and there are many sociological arguments to suggest that female criminals are treated more leniently. On the other hand, some sociologists believe women are treated more harshly when they commit certain types of crime. This essay aims to assess the reasons for gender differences in reported crime rates.

Missing values were replaced by the average of all the other items in that scale for that individual respondent. Analyses were conducted to determine if the mean scores for individual items were significantly different (less than or greater) from zero, the neutral response value—signifying either statistically significant disagreement or agreement with an item, respectively. Next, a factor analysis was performed to determine if similar items clustered together into subscales. Descriptive statistics (means and standard deviations) and one sample, two-tailed t-tests were calculated for each resulting subscale (Butler, 2010).

Crime can be described as an act that harmful to an individual as well as the society; such acts are against and punishable by the law. While deviance can be described as acting against social norms, for example a boy wearing a skirt would be out of place in the society

With the trend of globalization, different people from different cultural background can interact with each other in one community. This can be reflected in UCSB. UCSB's students were known for their academic success as well as racial diversity. In 2014-2015 academic year, undergraduates racial distribution for "White is 39%; Asian/Pacific Islander Subtotal is 27%, and Black/ African American is 4%" (2014-2015 Campus Profile). Students with different cultural background came here to pursue educational success. While their races are different, most of them have one thing in common, they are here to study. We are interested to see the relation between race, gender, and study behavior. We developed our research question and tried to understand

An Impressive body of research examines race-related stereotypes in advertising. By the means of content analyses, these studies have served as a “barometer” of the evolution of the representations over time. African-American sources went from unskilled laborers to racial equality via subtle portrayals of socioeconomic inferiority. Nonetheless, the use of certain stereotypes remains consistent over time. In the United States, such representations include African Americans as athletes and entertainers and Asian Americans as technologically savvy. (Johnson/Grier, 92) However the way someone reacts to racial stereotypes depends on their own outlook on the subject. (Johnson/Grier,

To determine if there was a difference in fallout rates between white males and females by race as well as other nonwhite males, a set of one-sample t-tests was used. Table 6 presents a comparison of white males to females by race and nonwhite males. For females, the test indicated that the white males’ (20.28) fallout rate was sig-nificantly lower than fallout rates for Black females (M = 21.84, SD = 0.85), t(4) = 4.12, p =.015, d = 0.82 and significantly greater white females (M = 18.87, SD = .075), t(4) =-4.19, p = .014, d = -.84, but was not signifi-cantly different from Hispanic females (M = 21.28, SD = 1.23), t(4) = 1.82, p = .143, d = 0.36; Native American females (M = 22.56, SD = 3.74), t(4) = 1.37, p = .244, d = 0.27; and Asian females (M = 21, SD = 1.22), t(4) = 1.32, p = .258, d = 0.26. For males, the test indicated that white males’ fallout rate was significantly less than fallout rates for Black males (M = 22.86, SD = .099), t(4) = 5.85, p =.004, d = 1.17; Hispanic males (M = 22.25, SD = 1.14), t(4) = 3.86, p = .018, d = 0.77; but was not significantly different from Native American males (M = 24.16, SD = 3.99), t(4) = 2.18, p = .095, d = 0.44 and Asian males (M = 21.57, SD = 1.30), t(4) = 2.21 p =.091, d = 0.44.

Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences to the humanities. Statistics are also used for making informed decisions – and misused for other reasons – in all areas of business and government. Statistical methods can be used to summarize or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and then used to draw inferences about the process or population being studied; this is called inferential statistics. Both