9.3C: The Upper Middle Class (2024)

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    The upper-middle class refers to people within the middle class that have high educational attainment, high salaries, and high status jobs.

    Key Points

    • Members of the upper-middle class have substantially less wealth and prestige than the upper class, but a higher standard of living than the lower-middle class or working class.
    • The U.S. upper-middle class consists mostly of white-collar professionals who have a high degree of autonomy in their work. The most common professions of the upper-middle class tend to center on conceptualizing, consulting, and instruction.
    • In addition to having autonomy in their work, above-average incomes, and advanced educations, the upper middle class also tends to be powerful; members are influential in setting trends and shaping public opinion.

    Key Terms

    • educational attainment: Educational attainment is a term commonly used by statisticians to refer to the highest degree of education an individual has completed.
    • salaried professionals: White-collar employees whose work is largely self-directed and is compensated with an annual salary, rather than an hourly wage.

    Sociologists use the term “upper-middle class” to refer to the social group consisting of higher-status members of the middle class. This is in contrast to the term “lower-middle class,” which is used for the group at the opposite end of the middle class stratum, and to the broader term “middle class. ” There is considerable debate as to how to define the upper-middle class. According to the rubric laid out by sociologist Max Weber, the upper-middle class consists of well-educated professionals with graduate degrees and comfortable incomes.

    In 1951, sociologist C. Wright Mills conducted one of first major studies of the middle class in America. According to his definition, the middle class consists of an upper-middle class, made up of professionals distinguished by exceptionally high educational attainment and high economic security; and a lower-middle class, consisting of semi-professionals. While the groups overlap, differences between those at the center of both groups are considerable.

    Among modern sociologists, the American upper-middle class is defined using income, education, and occupation as primary indicators. There is some debate over what exactly the term “upper-middle class” means, but in academic models, the term generally applies to highly educated, salaried professionals whose work is largely self-directed. The U.S. upper-middle class consists mostly of white-collar professionals who have a high degree of autonomy in their work. The most common professions of the upper-middle class tend to center on conceptualizing, consulting, and instruction. They include such occupations as lawyer, physician, dentist, engineer, professor, architect, civil service executive, and civilian contractor. Many members of the upper-middle class have graduate degrees, such as law, business, or medical degrees, which are often required for professional occupations. Educational attainment is a distinguishing feature of the upper-middle class. Additionally, household incomes in the upper-middle class commonly exceed $100,000, with some smaller one-income earners earning incomes in the high 5-figure range.

    In addition to autonomy in their work, above-average incomes, and advanced educations, the upper middle class also tends to be powerful; members are influential in setting trends and shaping public opinion. Moreover, members of the upper-middle class are generally more economically secure than their lower-middle class counterparts. Holding advanced degrees and high status in corporations and institutions tends to insulate the upper-middle class from economic downturns. Members of this class are likely to be in the top income quintile, or the top 20% of the economic hierarchy.

    9.3C: The Upper Middle Class (1)
    9.3C: The Upper Middle Class (2024)

    FAQs

    Why is it important to check the 10% condition before calculating probabilities involving? ›

    It's important to check the 10% condition before calculating probabilities involving x because we want to ensure that the observations in the sample are close to independent.

    What effect does violating the 10% condition have on the standard deviation of the sampling distribution of? ›

    b) When the 10% condition is violated, it can lead to an inflated standard deviation of the sampling distribution of the sample mean. This means that the estimate of the average amount of time spent looking at a screen per day may have higher variability due to the smaller sample size relative to the population size.

    What sample size would be required to reduce the standard deviation to one half? ›

    To reduce the std dev by ½ we would have to multiply the sample size by 4; we would need to sample (1012)(4) = 4048 adults. (f) If the pollsters had surveyed 1012 teenagers instead of 1012 adults, do you think the sample proportion ˆp would have been greater than, equal to, or less than 0.67?

    What sample size would be required to reduce the standard deviation of the sampling distribution to one third the value you found in exercise 36b? ›

    To determine the sample size required to reduce the standard deviation of the angles distribution to one-third the value found in exercise 36(b). Therefore, a sample size of 9 would be required to reduce the standard deviation of the sampling distribution to one-third the value found in exercise 36(b).

    How to verify the 10 condition is met? ›

    Step 1: Identify the population size, , and calculate 10% of the population size, . Step 2: Identify the sample size, . Step 3: Compare the sample size to 10% of the population size. If n ≤ 0.1 N then the 10% rule is satisfied.

    What happens if the 10 condition is not met? ›

    Since the sample size is greater than 10% of the population size, the 10 percent rule is not met and the teacher cannot act as though the condition for independence is met. In order to act as if independence is met, the sample size would need to be 20 (10% of 200) or smaller.

    Why is the 10 condition important? ›

    The 10% condition in statistics stipulates that when sampling without replacement, the sample size should not be more than 10% of the population. This rule helps prevent bias in statistical results, especially in studies where sampling plays a crucial role.

    What is the large counts condition to use a normal distribution? ›

    When the sample size n is large, the sampling distribution of p is close to a Normal distribution with mean p and standard deviation √p(1 − p)/n. In practice, use this Normal approximation when both np ≥ 10 and n(1 - p) ≥ 10 (the Large Counts condition).

    How to check large counts condition? ›

    The Large Counts condition When constructing a confidence interval for a population proportion, we check that both n p ∧ and n 1 - p ∧ are at least. a.

    What does the large counts condition state? ›

    The large counts condition, also known as the "success-failure" condition, is used when applying certain statistical methods to categorical data. It states that for these methods to be valid, both the number of successes and failures must be at least 10.

    What is the 10% condition in stats? ›

    The 10% condition states that sample sizes should be no more than 10% of the population. Whenever samples are involved in statistics, check the condition to ensure you have sound results. Some statisticians argue that a 5% condition is better than 10% if you want to use a standard normal model.

    Which is more surprising, getting a sample of 25 candies in which 32% are orange or getting a sample of 50 candies in which 32% are orange? ›

    Which is more surprising: getting a sample of 25 candies in which 32% are orange or getting a sample of 50 in which 32% are orange? A sample of 50, because we expect to be closer to p=0.45 in larger samples.

    Does Harvard College alcohol study find that 67% of college students support efforts to crack down on underage drinking? ›

    The Harvard College Alcohol Study finds that 67% of college students support efforts to "crack down on underage drinking." The study took a random sample of almost 15,000 students, so the population proportion who support a crackdown is close to p = 0.67.

    What sample size is needed for standard deviation? ›

    There is no “right” standard deviation that comes from the “correct” number of samples. There is only the law of large numbers and the rule of thumb that is 30 samples.

    Why does sample size affect standard deviation? ›

    As the sample size increases, n goes from 10 to 30 to 50, the standard deviations of the respective sampling distributions decrease because the sample size is in the denominator of the standard deviations of the sampling distributions.

    What is the 10 percent sampling rule? ›

    The 10% rule states that a sample size should not exceed 10% of the population when using sampling methods like simple random sampling. This helps ensure that the sample is representative of the population.

    What happens to the capture rate of the 10 condition is violated? ›

    If the 10% condition (without replacement) is violated, then the confidence intervals are longer than they need to be, meaning that the actual capture rate is greater than what is indicated in the confidence level.

    Why do we check the large counts condition? ›

    The large counts condition ensures that the distribution of the sample proportion is approximately normal, which is a key assumption when constructing confidence intervals using the normal approximation.

    Why is it important to consider probabilities in statistical analysis? ›

    We use probability to quantify how much we expect random samples to vary. This gives us a way to draw conclusions about the population in the face of the uncertainty that is generated by the use of a random sample.

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