# Confidence intervals

A 95% confidence interval is usually sufficient for sample estimates of most opinion polls or population parameters. If the level of confidence increases, then the confidence interval becomes less precise (widens). Choosing between 95% and 99% is a trade-off between reducing risk (and increasing confidence) versus the width of the interval.

For example, in the chapter exercises, Question #3 is about opinions on global warming. The data show that 589 out of the 1,511 surveyed felt global warming is a very serious problem. When calculating the proportion of respondents, the 95% confidence  interval is between 0.365 to 0.415, and the 99% between 0.356 to 0.424. In this particular case, the intervals have a very small difference. Is there a good rationale for choosing 95% versus 99%? I think the discussion context might matter here more than the numbers. A news article seems okay for reporting the 95% confidence interval. A high-level administrator trying to make an evidence based decision about federal environmental science investments might want to use the 99% (or even 99.9% for a large budget worth billions of dollars).

The other two factors involved in choosing a confidence interval might be sample size and sample standard deviation. A larger sample size increases the precision of the confidence interval (narrows), but also increases time and cost for the survey. A higher sample standard deviation decreases the precision of the confidence interval (widens). Both of these might affect choosing between the result of a 95% confidence interval vs 99% as well as the reporting venue.

For a 99.9% confidence interval, this means that the researcher really wants to be as close to 100% as possible (since 100% doesn’t actually seem possible in estimation). Health decisions might fit within this category, such as estimating the spread of deadly diseases in the country, as well as ones involving billions of dollars. If there’s a rule of thumb for using a certain percent, I haven’t come across it and probably won’t because it’s too dependent on context.

For an internet resource, I looked at Stattrek: http://stattrek.com/estimation/confidence-interval.aspx. I’ll admit what drew me in is the similarity to Star Trek. Unfortunately, the website doesn’t use science fiction references or problem examples. The estimation section includes more on margin of error than our textbook, such as finding the critical value and expressing it as a t score (or z score). The section on confidence intervals is relatively short, simple, and compatible with our textbook. The estimation problems also go further than our text with regression slopes and calculating differences (between proportions, means, and matched data pairs).

# Week 7: sampling distributions

I started by looking at the Khan Academy on sampling distributions, however the first set of videos did not get covered by our textbook (sample proportions), so I skipped ahead to the sample means section. The central limit theorem video presents a simplified explanation similar to the textbook. The sampling distribution of the sample mean video continues by illustrating the central limit theorem and also adds definitions of skew (covered under measures of central tendency)/kurtosis (new concept). The Khan Academy videos don’t take theories for granted and instead attempt to prove them with examples using simple math written on a virtual chalkboard, such as how increasing the sample size creates a more normal sampling distribution. Although the textbook provides much more detail in the space of several pages, these videos spend about ten minutes going in-depth on one concept. Khan tends towards using variance (while explaining standard deviation as its square root), which may be an individual preference? In addition, the videos tend to summarize and reinforce the prior concepts.

The Khan Academy’s lessons have been organized differently than the textbook. For example, I found some videos about constructing probability distributions in the random variable section. He adds confidence intervals (the next chapter in our textbook) and showing the difference between two sample mean distributions (which is the sum of their variances) within the sampling distribution section as well as sampling proportions (where I had to look up Bernoulli). Sampling proportions seemed confusing to me, especially because the textbook does not cover it. I also found some discussion of the sampling methods in a sampling and surveys section.

Then, I took a look at an academic website in the hopes that it might match our textbook better with online lessons by Penn State. This resource also turned out to have videos to demonstrate examples using a stats program (Statkey rather than SPSS). It also had a section for sampling proportions and an introduction to the t distribution (similar to the standard normal distribution but with varied heights). In comparison, I think the Khan Academy videos make the subject more approachable for everyone without losing too much information although they make a better starting point than an ending.

# Conflict theory and the digital economy

Using the lens of conflict theory, digital technology has seemingly made it easier for workers to be exploited by corporations or app makers. The Digital Labor and Imperialism article viewed the digital age as spawning a new era of imperialism domestically as well as internationally, using the example of Apple iPhones. Fuchs described the plight of the Chinese worker required to work 60 hours a week (also a racist standard) and earning \$5 per phone sold, while Apple makes a profit of \$175 from the purchase price of \$299. Apple and other corporations would argue that the “profit” pays for technology development, software development, extensive testing, and other processes necessary to even create a product for manufacture (thus needing the worker).

The gig economy article attempted to keep a positive spin on Uber’s interactions with its contractors by recommending more transparency and possible technology fixes for common complaints. Uber might be exploiting its contractors through inconsistent policies (wait time and cancellation fees), guaranteed wages (unclear who gets offered these opportunities), and technology glitches. This discussion leaves the reader with the distinct impression that the corporation has not prioritized fixing these issues, therefore does not value its workers as much as customer service and profits.

How would either situation be good for society? What progress (or the opposite) is made from the conflict? In the first scenario, societal globalization may be the eventual destination emerging from economic globalization. We’ve been seeing the results of a limited cultural exchange for centuries, such as the import of European fashions or the export of Hollywood movies. As corporations seek to find cheap labor, the worker’s plight extends to these areas and new bonds form between the working classes of both countries (eventually, after the initial objections about losing jobs overseas). From a Marxist perspective, a critical mass of worker consciousness around the globe might kick start the revolution? From an organizational view, companies have gained economic power by sourcing cheaper labor and possibly avoiding corporate taxes for moving their facilities elsewhere as well as political power to lobby for corporate incentives. In China, these jobs might be very desirable because the alternatives have even worse pay or hours (which makes our capitalist imperialism seem even more despicable).

For the second scenario, I’ve seen arguments that the transportation gigs have done well in areas with poor infrastructure (taxis or other public alternatives). The conflict between the company and its drivers exists because of a larger issue within a metropolitan area and its available services. From a Weberian perspective, the availability and affordability of these services reinforces the social strata of the riders. From a Marxist view, the drivers bear the brunt of the physical (possibility of accidents) and economic risk (taxes and maintenance costs as subcontractors) while the company reaps the profits from their work. Uber’s goal to employ a fleet of self-driving cars also threatens the economic incentive to workers. If the company pays people for being “backups” to the self-driving system rather than actually driving, then wages might be cut because the workers technically need to do “less” work. Technology is not helping resolve class conflict, but making it worse!

# Week 4-5 social stats

Using the GSS2014 data file, I came across two variables related to astrology:

1. Do you ever read a horoscope or your personal astrology report?
• Answers: yes or no. Other responses: don’t know, no answer, or not applicable.
2. Would you say that astrology is very scientific, sort of scientific, or not at all scientific?
• Scale: very scientific, sort of scientific, or not at all scientific. Other responses: don’t know, no answer, or not applicable.

Working backwards (having found my variables first), my research questions might ask: How popular is pseudoscience in United States? Do Americans tend to recognize the difference between science and pseudoscience? More specifically, how does a person’s belief in astrology relate to their belief in science? I remember seeing the results of a poll in a news article that indicated some non-zero number of people mistook astrology for astronomy. The ramification for this question includes public understanding of science as well as public support for science and scientific research. This topic also may have relevance to beliefs on larger and more controversial issues, such as climate change.

For the first variable, slightly more people responded that they did not read a horoscope or personal astrology report (55.5% to 44.5%). Presumably, of those that did admit to reading their horoscope, only 32.6% responded either very or sort of scientific (395 responses). It seems very unlikely that someone who would not read astrology, would answer sort of or very scientific for the second question. 67.4% responded that it is not at all scientific (818 responses). Both questions had a surprisingly high “not applicable” response (marked as “missing”), which is slightly more than half of the total survey respondents.

Since the results should be generalizable, this comfortingly indicates that slightly more than half of public completely ignores astrology. Of the astrology readers, one-third believes that astrology has a little or a lot of basis in science, which may make them excellent targets for infomercials selling miracle products. This is fortunate for the manufacturers of modern day snake oil and the astrology industry. However, two-thirds do not believe that astrology has a basis in science. Two-thirds is greater than the half from the first question, so some people do read their horoscope, but do not believe it has any basis in science (e.g. read it for entertainment).

The first variable results indicates that astrology is only popular with about half of the population, which provides one case study answer for the first research question by looking at the popularity of astrology as a psuedoscience. The second variable results provide a partial answer for the second research question that a majority of people (67%) do not believe in the pseudoscience of astrology and can differentiate it from actual science. These variables don’t give enough information to look at how a person’s belief in astrology relates to how they believe in science. It would be interesting to see what other things this subset of respondents believe is scientific and where they got their information from to form their beliefs.

# Durkheim

Emile Durkheim created the basis for the study of sociology as an academic field and structural functionalism theory. He sought to differentiate sociology as a science separate from psychology or biology, although his theory delves into the motivations of individuals and society. Durkheim’s work influenced theorists such as Talcott Parsons and rational choice theory became a direct challenge to the emphasis on the collective.

Society is sui generis relates to several different concepts, such as the system (society as a collective versus individuals) and how norms affects each level. The literal definition means “unique” and supports how cultures have fundamental differences in moral values and norms, such as suicide rates or religion. Social facts shape society through socialization and education, creating a collective conscience. Their impact on individuals, however, is often unconscious and helps control undesirable behavior (“anomie”).  He also examined the tension in societies from the division of labor, identified as mechanical (where needs of the many outweigh the few) versus organic (promoting individualism) solidarity (creation of social bonds). Frank Elwell described the difference between the question asked as “is this decision moral?” versus “how would this decision benefit me?”

Moral machines become an example of the uniqueness of cultures within society as well as the individual’s assimilation into a culture’s shared values. While rational choice theory clearly benefits the individual in a prisoner’s dilemma, Durkheim’s world is more and less predictable. If the cultural norms dictate one outcome, individuals presumably would choose the same choice because they have internalized the same collective values and morality. However, Durkheim allowed for a disconnect between individuals and society that causes individuals to be detached enough from the collective to make a different choice. MIT’s Moral Machine project attempts to collect perspectives on how people would choose to act based on two terrible scenarios. For example, the technology of self-driving cars requires programming that might present a scenario that involves protecting its occupant or a pedestrian. What if the pedestrian is a mother with a baby in a stroller? Should the software value two lives over one? Or babies/children over adults?

Several major assumptions made seems to be about the level of culture and possibility of interaction between cultures. Families may have unique traditions (especially around the holidays), which many other families might share, but what level of commonness becomes a collective level of culture rather than more “individual” (if we count each family as an individual unit. Social facts must be considered in an objective context, however, the emphasis on morality does not have ethical implications other than what the culture collective accepts. Eating dogs as meat might exist as a norm in one culture, but horrifying in another. Eating any meat might disturb vegans who choose to avoid animal products, but is generally accepted by the majority, so the practice of cultivating animals for food continues as a robust industry.

Also, what happens when multiple cultures intersect, especially along international borders or diverse areas (such as Washington DC)? If we always exist as members of multiple groups, what happens when they conflict? For example, Democrats tend to support pro-choice legislation and side against the death penalty. Republicans tend towards the opposite and Independents claim to choose based on candidate or particular issues. “American politics” presents a neat label on this messy situation and rational choice theory starts making more sense. Durkheimian theory may not have room for “universal truths” or anything that claims to span every culture. In addition, what happens when enough deviance and anomie dominate a society? Durkheim accepted some amount of crime as a test for society to reaffirm its values. The rise of individualism logically leads to a change within society, which may become popularized into becoming accepted collectively and perhaps restarting the cycle?

# Week 3 stats assignment

Research question 1: Where does the public predominantly choose to get their information, such as on health or medical topics? Print journalism currently seems to be at a crisis point, as newspapers have seen declining subscriptions and bankruptcy in recent years. Competitors include television/cable news and online sources. The Internet also allows alternate forms of news dissemination through non-journalistic sources such as social media and blogs.

I analyzed the results from the following question, asked about each area:

How much attention do you pay to information about health or medical topics from: The Internet? National or cable television news? Print newspapers? (Scale: A Lot, Some, A Little, None)

From the scaled responses, individuals paid a lot of attention to information from online sources (20%), nearly five times that of television (6.1%) or print (4%). Slightly more individuals paid at least a little attention to online sources (81.5% cumulative) than television (78.9% cumulative) or print (71.9% cumulative).

This data seems to support that the more respondents chose to pay attention to online sources for information on health/medical topics and the least to print newspapers. Future research might look at other kinds of topics or ask a more general question.

Research question 2: How much do individuals trust doctors versus online sources? As an abundance of information is available online, individuals may choose to research their symptoms before going to a doctor. Once at the doctor’s office, patients may second guess their doctors to ask about various ailments or treatments that they found online. This is significant for possible effects on the quality of health care for both the doctor and patient.

I analyzed the results of the following questions:

In general, how much do you trust information about health or medical topics from: A Doctor? Internet? (Scale: A Lot, Some, A Little, Not At All)

From the scaled responses, individuals placed a lot of trust in doctors (68%) than the Internet (18.3%). More respondents said they had some trust for online information (53.6%). 98.4% said they trusted information from doctors at least a little, while 91.0% trust information from online at least a little. More respondents chose not at all for online information (8.5%) than doctors (1.5%).

This data seems to support that while medical information is easily available online, individuals still place higher trust in doctors than what they can research on the Internet. Future research might look at more specific questions, such as trusting information from doctors online (rather than encyclopedia type sites or ads), or perhaps trusting information from television sources.

# Hello world!

I’m excited to begin this digital sociology program since my research interests have intersected with “new media” in a previous life as a historian. I currently work full-time for the federal government and live near Washington DC.

Fun fact about me: I love coffee and coffee-flavored foods (such as ice cream), but usually drink decaf ever since my first pregnancy. Two kids later, I’m still drinking decaf and feel good most of the time about not being caffeine dependent…

Numeric data has been difficult to find to support my research interests on public opinion because polling provides very specific quantitative information with limitations. For example, a poll asking whether you support increased spending on space results in a fairly straightforward answer (% yes/no), but not why or even how much. On the other hand, several published editorials and letters to the editor with detailed arguments would not indicate whether the majority of the public supports it (or even is paying attention to the issue). This gets to the contrast between deductive and inductive research.

My concerns for taking a social stats course would be 1) learning new software, 2) whether this is math intensive in the context of not taking math as an academic subject for awhile, and 3) whether the first two factors make it very time intensive. I do hope to learn new skills and find out what kinds of different questions can be answered through statistical analysis.

## VCU Digital Sociology

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