A Nonparametric Test

Test scores of individuals outside of this age range would not be considered valid, since there would be no norms to compare the individual’s scores to. Fortunately, there are no gender limitations since the normative sample included both males and females equally at all ages and grades (Pearson, 2009b). The normative sample also included several ethnicities representative of the U.S. population. In addition, the developers intended to reduce cultural bias by adding pictures of multiple cultures in the demonstration illustrations (Pearson, 2009b). However, it is important to note no differential studies were conducted for gender or race and ethnicity (Miller, 2010). Furthermore, the test was only normed in English and has not been translated into any other language (Pearson, 2009b). This will make it difficult for clinicians to administer the test to individuals whose primary language is not

In American society today there is an imbalance in the gender income gap between men and women in the work force. Many factors such as discrimination, productivity, educational background and disproportional hours worked contribute to this ongoing challenge. While many are skeptical, others remain to have strong beliefs that women and men are treated equally. In most professions according to Glynn “women only earn seventy seven cents for every dollar earned by men” (2014). Although, the seventy seven cents figure does not accurately reflect gender discrimination, it does capture some discrimination,

According to Pager and Shepherd (2008), ‘Overall, then, the literature points toward consistent evidence of discrimination in access to employment, but less consistent evidence of discrimination in wages.” Levels of income vary from person to person depending on a variety of advantages such as education and experience. However, income differences also can depend on age, gender and race. There are numerous studies that show the significance of race discrimination affects wages or income.

The gender wage gap has been around since women began having jobs and careers. Though in the beginning the gender wage gap was purely do to discrimination by social stereotypes, now it has become more complicated than that. The issue today has evolved into a complex issue which combines our American culture with business economics. As a result, some are skeptical of the issue and some are very adamant in their beliefs. The issue encompasses not only gender stereo types but also educational, government policies and business’s best practices.

In a 2015 study, it is shown that the wage gap can even seem to increase at higher degrees of education. For men and women with less than a high school diploma, the wage gap is at about 20%. Surprisingly, for men and women with an advanced degree, the wage gap is 26%. While The wage gap steadily closed at a relatively rapid pace between the 1960s and 1990s, improving from a 60 percent gap to a 71 percent gap. But since 2000, progress has all but flatlined. Men earned $50,400 at the median in 2014, while women earned $39,600. Neither gender has seen a significant increase in their median earnings since 2009, and women’s 2014 median earnings were not statistically different than what they made in 2007. In conclusion, this is a big issue across the nation, and shown by statistics, not much has been done in the recent

According to the above results from MINITAB, the p-value of 0.038 is smaller than the significance level of 0.05; consequently, the null hypothesis will be rejected. There is sufficient evidence to support the

Many believe that those who don't have education can’t have wages that are higher than a minimum wage job. In some cases this is true but Hispanics and blacks who have received the same amount of education in a certain field to those of the Asian and White races still make less. However, looking just at those with a bachelor’s degree or more education, wage gaps by gender, race and ethnicity persist. College-educated black and Hispanic men earn roughly 80% the hourly wages of white college educated men ($25 and $26 vs. $32, respectively). White and Asian college-educated women also earn roughly 80% the hourly wages of white college-educated men ($25 and $27, respectively). However, black and Hispanic women with a college degree earn only about

The analysis of the data was done by employing the following statistical techniques which were chosen only after the investigator found them to be most appropriate and compatible to the data. Each statistical method is based upon its own specific assumptions regarding the nature of the sample, its universe and research conditions. These factors were considered in advance. Following statistical measures were

___IV. Practical Aspects - This book tells who the test is intended for and its standardized representative sample

The t-test for independent means was used to compute the average scores of one or more variables between the two unrelated groups (between groups). The participants were tested once. The researcher conducted an independent t-test to compare group means

In addition, in Lab #2 titled “Education, Occupation, Race and Wages” the study focuses on education and wages. The median annual wage for a person with a Bachelor’s degree is $24,128 higher than a person with just a high school degree alone. To expand on that statistic, a person who furthered their career and earned a Master’s degree earns a median annual wage of $11,648 more than a person with just a Bachelor’s degree. Education is not the only leading factor to income inequality -technology plays a key role also.

For many years now it has been assumed that men are paid more than women are paid in many occupations in many countries. We often question, why there is a pay gap between men and women especially if they are performing the same job? Economist Francine Blau and Lawrence Kahn took a set of human capital variables such as education, labor market, experience, and race into account and additionally controlled for occupation, industry, and unionism. While the gender wage gap was considerably smaller when all variables were taken into account, a substantial portion of the pay gap remained unexplained. These unexplained gaps are evidence of discrimination, which remains a serious problem for women in the workforce. In a standpoint refusing discrimination,

* The p-value= 0.282. The p-value is another complementary and equally valid way we can evaluate the null and alternative hypotheses is by looking at the p-value and compare the p-value to alpha. If the p-value is less than alpha, reject the null hypothesis and accept the alternative

In this case, level of significance, α was not provided. Therefore, the analysis will be evaluated based on two α values which are:

The Big Five test also goes in line with the nomothetic approach in the sense that it is a quick self test questionnaire which is quantitative. Each answer made in the test is a closed answer so the manager can expect answers to be within a certain paradigm as opposed to an open questions test where the subject can give any random answer that the manager is not expecting.