## The U.S. government keeps statistics on many people in America. One interesting statistic is the poverty rate

The U.S. government keeps statistics on many people in America. One interesting statistic is the poverty rate. To be living in poverty, one must earn income below a certain threshold (approximately $900 per month). Many multimillionaires are included in this statistic. Recently, Barbara Streisand was “living in poverty.” In a particular year, she did not perform live, and her album sales were extremely slow. She has a great deal of wealth but had little income that year. Although she has more money than 99.99% of the rest of the population, according to the government income threshold, she was considered to be impoverished. What other statistic can you name that is misleading? Why?

## Verified Expert Answer

Statistics play a vital role in determining the current state of affairs within a country or a region. Through statistics, we can easily make predictions that impact society even in the long run (Makridakis et al., 2018). However, when the information is not accurate, statistics can be a source of confusion. As indicated, one of the statistics that at times can provide misleading interpretation of the statistics on income levels, where for those who are not on payroll, the statistics capture them to live below poverty rates which in a real sense may not be the case.

Another example is the unemployment rate. with unemployment rate, the statistic usually does not factor in everyone who does not have a job, and therefore not an accurate measure of joblessness. As such, statistics experts often use real unemployment rates to estimate the real statistics on joblessness (Cardoso & Ferreira, 2009). The common unemployment rate often fails to consider various groups of people when making calculations. For example, it does not consider whether an individual is working full-time or part-time.

It also fails to consider persons who are working as freelancers and those in informal employment. Therefore, based on these aspects, the unemployment rate as a statistical figure can be misleading.

**References**

Cardoso, A. R., & Ferreira, P. (2009). The dynamics of job creation and destruction for University graduates: why a rising unemployment rate can be misleading. *Applied Economics*, *41*(19), 2513-2521.

Makridakis, S., Spiliotis, E., & Assimakopoulos, V. (2018). Statistical and Machine Learning forecasting methods: Concerns and ways forward. *PloS One*, *13*(3), e0194889. https://doi.org/10.1371/journal.pone.0194889

### Alternative Answer

Unfortunately, this is a very broad subject because statistics that are quoted and presented to us on a regular basis are often misleading. Anything from political statistics to consumer information can be skewed simply by misuse of statistical data or by poor methods used to gather the data to begin with. According to a Forbes article on the subject, “Beyond the obvious candidates like suggestions of correlation implying causation and improper use of statistical techniques, perhaps one of the greatest enablers of fake news …is sampling bias and selective definitions” (Leetaru, 2017) .

One subject that is notorious for being prone to data misuse is crime statistics. We are often fed alarming information saying crime is rising or assuaged saying crime is declining, but crime statistics are much more complex than that. Is it ALL crime that is on the rise (unlikely), or only certain crimes? White collar crimes, violent crimes, etc? A rise in homicides is a much different issue than a rise in identify theft, for example.

It is our job as consumers of information to be critical thinkers and check the sources of studies when we are alarmed by information that we are presented with before being reactive. “As the United States grapples with an epidemic of gun violence and these reverberating impacts of homicide, it will take better research, consistent data collection and community-tailored approaches to understand and address the roots of violent crime. In the meantime, we can all benefit from a more critical, humane and nuanced understanding of how complicated crime data really is” (Krishnakumar, 2021).

Source:

Leetaru, K. (2017, February 3). *Lies, damned lies and statistics: How bad statistics are feeding fake news*. Forbes. https://www.forbes.com/sites/kalevleetaru/2017/02/02/lies-damned-lies-and-statistics-how-bad-statistics-are-feeding-fake-news/?sh=27b90c9850ca

Krishnakumar, P. (2021, July 14). *How crime stats lie – and what you need to know to understand them*. CNN. https://www.cnn.com/2021/07/14/us/crime-data-reporting-united-states-homicide-increase/index.html

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### Other Questions Related to this Class:

**Topic 1 DQ 2**

You just saw a commercial for the Tread Master, an exercise machine that claims an average weight loss of 10 pounds. A commercial for the Climber, a competing product, claims that only 1 out of 10 users of the Tread Master lost any weight at all. The rest of them gained weight. How can both of these claims be true?

**Topic 2 DQ 1**

The definition of a *probability* is stated as: A measure of the likelihood that an event in the future will happen; it can only assume a value between 0 and 1, inclusive. Explain the meaning of the 0 and 1.

**Topic 2 DQ 2**

You are looking for a home in a particular neighborhood, and you want to know the typical number of bathrooms and bedrooms, the square footage, and the appraised value of houses in that neighborhood. Which measure of central tendency (mean, median, or mode) would be the most appropriate for each piece of information listed and why?

**Topic 3 DQ 1**

Provide some examples of discrete and continuous variables. What attributes of these variables make them discrete and continuous? Why?

**Topic 3 DQ 2**

Describe the term *mutually exclusive.* Provide some examples. Must the values of *x* in a discrete probability distribution always be mutually exclusive? Why or why not? Provide an example.

**Topic 4 DQ 1**

You just saw an ad on television that states the majority of the population would vote to make smoking illegal. The poll that is referenced shows 53% of those asked supported making smoking illegal. In the fine print at the bottom of the screen, you see that the margin of error is +/- 3%. What is your reaction? Explain.

**Topic 4 DQ 2**

As the marketing director of Harley-Davidson, you need to determine what your customers would like in the next model. You put a survey on the Harley website. Is this a good frame from which to select your sample? Explain.

**Topic 5 DQ 1**

Your mayor just announced that the local unemployment rate dropped last month from the prior month. It went from 10.5% to 10.4%. Is this a significant drop? Explain.

**Topic 5 DQ 2**

Give an example of a situation in which you believe a Type I error is more serious than a Type II error. Give an example of a situation in which you believe a Type II error is more serious than a Type I error. In each case, why do you think so?

**Topic 6 DQ 1**

What does the *p*-value tell the business statistician, especially in terms of the normal curve? If the *p*-value is smaller than the level of significance, what does that mean in terms of the null hypothesis? Why?

**Topic 6 DQ 2**

A research firm tracks the average highway speed of 30 drivers driving home on Day 1. For the next 10 days, the drivers are given two cups of coffee 1 hour before the drive home. On the 10th day, the average highway speed is measured again. Does this study involve dependent or independent samples? You are interested in knowing if there is a statistical difference in driving speeds between Day 1 and Day 10. Which statistical test would be appropriate? Why?

**Topic 7 DQ 1**

Provide an example of where you could use correlation in real life. Explain why a t-test is necessary before you accept this correlation as being real in the population.

**Topic 7 DQ 2**

Compare the Spearman and Pearson correlations.

**Topic 8 DQ 1**

In ANOVA analysis, what is the real meaning of the term *treatment*? What does this really mean? Provide some examples of treatments from a business or managerial perspective.

**Topic 8 DQ 2**

How many different tests does the textbook give you for applying the chi-square distribution? What are these tests? How could you use each of these tests at your place of business?