"It’s only when the tide goes out that you learn who has been swimming naked." ---Warren Buffett
Please comment on this statement and give examples from previous accounting scandals and financial crises.
Initial Post Length: minimum of 350 words.
Using APA format, cite your sources.
In: Finance
Why should each department participate in preparing its own budget? How much control do you think each department should have? Does your answer differ for when considering a service firm versus a manufacturing firm? Please answer in 350 words or more. Please add examples
In: Accounting
Why should each department participate in preparing its own budget? How much control do you think each department should have? Does your answer differ for when considering a service firm versus a manufacturing firm?
Please answer in 350 words or more. Please add examples
In: Accounting
Compute and tabulate full-station elevations for an unequal-tangent vertical curve to fit the requirements in Problems 2 through 5.
4. Grades g1 of +5.00% and g2 of -2.00%, meet at the VPI at station 4+300 and elevation 154.960 m. Lengths of curves are 200 and 350 m. (Use 40-m stationing)
In: Civil Engineering
A domestic wastewater with a flow of 1700 m3 / day will be treated in a biological treatment plant. Wastewater pre-settling tank effluent BOD value is 350 mg / L. If the volume of the biological reactor (ventilation reactor) is 500 m3, do you prefer a fully mixed or plug-flow reactor? Please explain the reasons.
In: Civil Engineering
I need to make 2 possible suggestions on how Comcast can fix the problem with their customer service, and how Comcast can possibly improve the whole business overall while briefly discussing the impacts of these suggestions.
Please put in a paragraph with the heading above, I Must come up with 350 words in total.
In: Operations Management
The Atlantic Article
The Myth of 'I'm Bad at Math'
Basic ability in the subject isn't the product of good genes, but hard work.
Miles Kimball, Noah Smith and Quartz
October 28, 2013
“I’m just not a math person.”
We hear it all the time. And we’ve had enough. Because we believe that the idea of “math people” is the most self-destructive idea in America today. The truth is, you probably are a math person, and by thinking otherwise, you are possibly hamstringing your own career. Worse, you may be helping to perpetuate a pernicious myth that is harming underprivileged children—the myth of inborn genetic math ability.
Is math ability genetic? Sure, to some degree. Terence Tao, UCLA’s famous virtuoso mathematician, publishes dozens of papers in top journals every year, and is sought out by researchers around the world to help with the hardest parts of their theories. Essentially none of us could ever be as good at math as Terence Tao, no matter how hard we tried or how well we were taught. But here’s the thing: We don’t have to! For high-school math, inborn talent is much less important than hard work, preparation, and self-confidence.
How do we know this? First of all, both of us have taught math for many years—as professors, teaching assistants. Again and again, we have seen the following pattern repeat itself:
Thus, people’s belief that math ability can’t change becomes a self-fulfilling prophecy.
The idea that math ability is mostly genetic is one dark facet of a larger fallacy that intelligence is mostly genetic. Academic psychology journals are well stocked with papers studying the world view that lies behind the kind of self-fulfilling prophecy we just described. For example, psychologist Patricia Linehan writes:
A body of research on conceptions of ability has shown two orientations toward ability. Students with an Incremental orientation believe ability (intelligence) to be malleable, a quality that increases with effort. Students with an Entity orientation believe ability to be nonmalleable, a fixed quality of self that does not increase with effort.
The “entity orientation” that says “You are smart or not, end of story,” leads to bad outcomes—a result that has been confirmed by many other studies. (The relevance for math is shown by researchers at Oklahoma City who recently found that belief in inborn math ability may be responsible for much of the gender gap in mathematics.)
Psychologists Lisa Blackwell, Kali Trzesniewski, and Carol Dweck presented these alternatives to determine people’s beliefs about intelligence:
They found that students who agreed that “You can always greatly change how intelligent you are” got higher grades. But as Richard Nisbett recounts in his bookIntelligence and How to Get It, they did something even more remarkable:
Dweck and her colleagues then tried to convince a group of poor minority junior high school students that intelligence is highly malleable and can be developed by hard work…that learning changes the brain by forming new…connections and that students are in charge of this change process.
The results? Convincing students that they could make themselves smarter by hard work led them to work harder and get higher grades. The intervention had the biggest effect for students who started out believing intelligence was genetic. (A control group, who were taught how memory works, showed no such gains.)
But improving grades was not the most dramatic effect, “Dweck reported that some of her tough junior high school boys were reduced to tears by the news that their intelligence was substantially under their control.” It is no picnic going through life believing you were born dumb—and are doomed to stay that way.
For almost everyone, believing that you were born dumb—and are doomed to stay that way—is believing a lie. IQ itself can improve with hard work. Because the truth may be hard to believe, here is a set of links about some excellent books to convince you that most people can become smart in many ways, if they work hard enough:
So why do we focus on math? For one thing, math skills are increasingly important for getting good jobs these days—so believing you can’t learn math is especially self-destructive. But we also believe that math is the area where America’s “fallacy of inborn ability” is the most entrenched. Math is the great mental bogeyman of an unconfident America. If we can convince you that anyone can learn math, it should be a short step to convincing you that you can learn just about anything, if you work hard enough.
Is America more susceptible than other nations to the dangerous idea of genetic math ability? Here our evidence is only anecdotal, but we suspect that this is the case. While American fourth and eighth graders score quite well in international math comparisons—beating countries like Germany, the UK and Sweden—our high-schoolers underperform those countries by a wide margin. This suggests that Americans’ native ability is just as good as anyone’s, but that we fail to capitalize on that ability through hard work. In response to the lackluster high school math performance, some influential voices in American education policy have suggested simply teaching less math—for example, Andrew Hacker has called for algebra to no longer be a requirement. The subtext, of course, is that large numbers of American kids are simply not born with the ability to solve for x.
We believe that this approach is disastrous and wrong. First of all, it leaves many Americans ill-prepared to compete in a global marketplace with hard-working foreigners. But even more importantly, it may contribute to inequality. A great deal of research has shown that technical skills in areas like software are increasingly making the difference between America’s upper middle class and its working class. While we don’t think education is a cure-all for inequality, we definitely believe that in an increasingly automated workplace, Americans who give up on math are selling themselves short.
Too many Americans go through life terrified of equations and mathematical symbols. We think what many of them are afraid of is “proving” themselves to be genetically inferior by failing to instantly comprehend the equations (when, of course, in reality, even a math professor would have to read closely). So they recoil from anything that looks like math, protesting: “I’m not a math person.” And so they exclude themselves from quite a few lucrative career opportunities. We believe that this has to stop. Our view is shared by economist and writer Allison Schrager, who has written two wonderful columns in Quartz (here and here), that echo many of our views.
One way to help Americans excel at math is to copy the approach of the Japanese, Chinese, and Koreans. In Intelligence and How to Get It, Nisbett describes how the educational systems of East Asian countries focus more on hard work than on inborn talent:
1. “Children in Japan go to school about 240 days a year,
whereas children in the United States go to school about 180 days a
year.”
2. “Japanese high school students of the 1980s studied 3 ½ hours a
day, and that number is likely to be, if anything, higher
today.”
3. “[The inhabitants of Japan and Korea] do not need to read this
book to find out that intelligence and intellectual accomplishment
are highly malleable. Confucius set that matter straight
twenty-five hundred years ago.”
4. “When they do badly at something, [Japanese, Koreans, etc.]
respond by working harder at it.”
5. “Persistence in the face of failure is very much part of the
Asian tradition of self-improvement. And [people in those
countries] are accustomed to criticism in the service of
self-improvement in situations where Westerners avoid it or resent
it.”
We certainly don’t want America’s education system to copy everything Japan does (and we remain agnostic regarding the wisdom of Confucius). But it seems to us that an emphasis on hard work is a hallmark not just of modern East Asia, but of America’s past as well. In returning to an emphasis on effort, America would be returning to its roots, not just copying from successful foreigners.
Besides cribbing a few tricks from the Japanese, we also have at least one American-style idea for making kids smarter: treat people who work hard at learning as heroes and role models. We already venerate sports heroes who make up for lack of talent through persistence and grit; why should our educational culture be any different?
Math education, we believe, is just the most glaring area of a slow and worrying shift. We see our country moving away from a culture of hard work toward a culture of belief in genetic determinism. In the debate between “nature vs. nurture,” a critical third element—personal perseverance and effort—seems to have been sidelined. We want to bring it back, and we think that math is the best place to start.
After reading the Atlantic Article written by Miles Kimball, Noah Smith and Quartz, respond to the article taking into consideration on your take and your experience. Write Down your compromises and what is it that you can visualize will be the more challenging parts of data analytics in conducting a PHD research.
In: Economics
In a study of media usage versus education level (American Demographics, Vol. 17, No. 6), an index was used to measure media usage, where a measurement of 100 represents the U.S. average. Values above 100 represent above-average media usage.
| Media | |||||
| Education Level | Cable Network |
Prime-Time TV |
Radio | Newspaper | Magazine |
| Less than high school | 80 | 112 | 87 | 76 | 85 |
| High school graduate | 103 | 105 | 100 | 99 | 101 |
| Some College | 107 | 94 | 106 | 105 | 107 |
| College graduate | 108 | 90 | 106 | 116 | 108 |
| Source: From American Demographics, Vol. 17, No. 6. Reprinted with permission, copyright 1995 American Demographics, Ithaca, NY. | |||||
| Minitab Printout for Media/Education Data | |||||
| Analysis of Variance for Index | |||||
| Source | DF | SS | MS | F | P |
| Edu | 3 | 961 | 320 | 2.96 | 0.075 |
| Media | 4 | 5 | 1 | 0.01 | 1.000 |
| Error | 12 | 1299 | 108 | ||
| Total | 19 | 2264 | |||
(a) List the factors and the number of levels of each factor. (Select all that apply.)
media usage, with two levels
education level, with three levels
media type, with five levels
education level, with four levels
school, with four levels
media type, with four levels
(b) Assume there is no interaction between the factors. Use two-way
ANOVA and the following Minitab printout to determine if there is a
difference in population mean index based on education. Use
α = 0.1.
| STEP 1: |
State the hypotheses. No difference in population mean index according to education level. At least two education levels have different mean indices. All education levels have different mean indices. At least two types of media have different population mean indices. All types of media have different population mean indices. No difference in population mean index by media type. H1: ---Select--- All education levels have different mean indices. At least two education levels have different mean indices. No difference in population mean index according to education level. At least two types of media have different population mean indices. All types of media have different population mean indices. No difference in population mean index by media type. |
||||
|---|---|---|---|---|---|
| STEP 2: | Find the test statistic and P-value.
|
||||
| STEP 3: |
State your conclusion. At the 10% level of significance, ---Select--- do not reject OR reject H0 for education level. The data ---Select--- do not indicate any differences OR indicate differences in population mean index according to education level. |
(c) Determine if there is a difference in population mean index based on media. Use α = 0.1.
| STEP 1: |
State the hypotheses. At least two types of media have different population mean indices. All education levels have different mean indices. All types of media have different population mean indices. At least two education levels have different mean indices. No difference in population mean index by media type. No difference in population mean index according to education
level. H1: ---Select--- No difference in population mean index by media type. No difference in population mean index according to education level. All types of media have different population mean indices. All education levels have different mean indices. At least two education levels have different mean indices. At least two types of media have different population mean indices. |
||||
|---|---|---|---|---|---|
| STEP 2: | Find the test statistic and P-value.
|
||||
| STEP 3: | State your conclusion. At the 10% level of significance, ---Select--- do not reject OR reject H0 for media. The data ---Select--- do not indicate any differences OR indicate differences in population mean index according to media type. |
In: Statistics and Probability
In a study of media usage versus education level (American Demographics, Vol. 17, No. 6), an index was used to measure media usage, where a measurement of 100 represents the U.S. average. Values above 100 represent above-average media usage.
| Media | |||||
| Education Level | Cable Network |
Prime-Time TV |
Radio | Newspaper | Magazine |
| Less than high school | 80 | 112 | 87 | 76 | 85 |
| High school graduate | 103 | 105 | 100 | 99 | 101 |
| Some College | 107 | 94 | 106 | 105 | 107 |
| College graduate | 108 | 90 | 106 | 116 | 108 |
| Source: From American Demographics, Vol. 17, No. 6. Reprinted with permission, copyright 1995 American Demographics, Ithaca, NY. | |||||
| Minitab Printout for Media/Education Data | |||||
| Analysis of Variance for Index | |||||
| Source | DF | SS | MS | F | P |
| Edu | 3 | 961 | 320 | 2.96 | 0.075 |
| Media | 4 | 5 | 1 | 0.01 | 1.000 |
| Error | 12 | 1299 | 108 | ||
| Total | 19 | 2264 | |||
(a) List the factors and the number of levels of each factor. (Select all that apply.)
school, with four levels
education level, with three levels
education level, with four levels
media usage, with two levels
media type, with five levels
media type, with four levels
(b) Assume there is no interaction between the factors. Use two-way
ANOVA and the following Minitab printout to determine if there is a
difference in population mean index based on education. Use
? = 0.05.
| STEP 1: |
State the hypotheses. All types of media have different population mean indices. At least two types of media have different population mean indices. No difference in population mean index according to education level. All education levels have different mean indices. At least two education levels have different mean indices. No
difference in population mean index by media type. At least two types of media have different population mean indices. No difference in population mean index according to education level. All types of media have different population mean indices. At least two education levels have different mean indices. No difference in population mean index by media type. All
education levels have different mean indices. |
||||
|---|---|---|---|---|---|
| STEP 2: | Find the test statistic and P-value.
|
||||
| STEP 3: | State your conclusion. At the 5% level of significance, ---Select--- do not reject/reject H0 for education level. The data ---Select--- do not indicate any difference/indicate differences in population mean index according to education level. |
(c) Determine if there is a difference in population mean index based on media. Use ? = 0.05.
| STEP 1: |
State the hypotheses. No difference in population mean index by media type. All education levels have different mean indices. No difference in population mean index according to education level. All types of media have different population mean indices. At least two types of media have different population mean indices. At least two education levels have different mean indices. No difference in population mean index according to education level. At least two types of media have different population mean indices. No difference in population mean index by media type. All types of media have different population mean indices. All education levels have different mean indices. At least two education levels have different mean
indices. |
||||
|---|---|---|---|---|---|
| STEP 2: | Find the test statistic and P-value.
|
||||
| STEP 3: | State your conclusion. At the 5% level of significance, ---Select One--- reject/do not reject H0 for media. The data ---SelectOne--- do not indicate any differences/indicate differences in population mean index according to media type. |
In: Statistics and Probability
1.What is called "soda' in the Northeastern United States is known as "pop" in the U.S. Midwest . It is just referred to as "coke" in the U.S. South. This is an example of
| A. |
U.S. culture |
|
| B. |
generational culture |
|
| C. |
social culture |
|
| D. |
regional culture |
|
| E. |
country culture |
2.
_____________ is the most important factor to take into consideration while launching products in global markets.
| A. |
culture |
|
| B. |
design |
|
| C. |
pricing |
|
| D. |
language |
|
| E. |
distribution |
In: Economics