Consider what you learned about the significance of self-awareness in your intrapersonal and interpersonal communication. Reflect on course concepts you learned about in your textbook, and then offer a personal connection by identifying your core strengths and discussing how they might guide you to a career path.

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onparametric tests are used to test the hypotheses with nominal and ordinal data. These tests have less strict assumptions. They do not identify normally distributed populations or the sameness of variance. Some tests demand the independence of cases. Other tests are clearly made for situations with related cases. Nonparametric tests are the only ones which can be used with nominal data. In addition, they are the only ones that can technically be used correctly with ordinal data, despite the fact that parametric tests are usually utilized in this case. Nonparametric tests can also be in use for interval and ratio data, despite the fact that they trail some of the existing information. They are easy for understanding and using. It is true that parametric tests are extra effective when it is proper to use them, but even in such cases, nonparametric tests achieve 95 percent of efficiency. Because of this, if the parametric test has a sample of 95, it will have the same statistical testing power as a nonparametric test with a sample of 100. To sum up, parametric and nonparametric exams are applicable in one-of-a-kind stipulations and circumstances. Parametric tests use interval and ratio data and they are ideally used when their assumptions can be met while nonparametric tests do not need strict assumptions about population distributions and they are in use with weaker nominal and ordinal measures. The most frequently used tests and the importance of the nonparametric tests in their usage One-Sample tests We use one-sample tests when we have a single sample and we wish to test the hypothesis that it derives from a defined population. A number of nonparametric tests can be put-upon in a one-sample situation, but we must not forget the measurement scale and some other stipulations. When the measurement scale is nominal, or in other words classificatory only, we can use each binomial test and the chi-square (ꭓ2) one-sample test. The binomial test can be used if the population is viewed as only two classes (for example, female and male). The researchers opt for to use binomial tests when the size of the sample is small and the ꭓ2 test is not in a use. Chi-Square Test This is probably the most used nonparametric tests of significance. It is vitally valuable in tests which include nominal data, however, it can be also applied in situations with higher scales. The typical cases that it takes part of being the cases where the objects are separated in two or more nominal categories (for instance, “yes – no”, or “A>

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