BMGT 311: Assignment #4 Data Visualization

In week number 4, we discussed the importance of visualizing data to make it more understandable and understandable for your target audience.  For this assignment, I would like all of you to use the data below and visualize it.

1. Create a graph or chart using Excel or other graphing program

2. Copy the graph into PowerPoint

3. Load your PowerPoint to http://www.slideshare.com

4. Comment with your slideshare link

All final projects are to be submitted via slideshare, so this will give you the opportunity to get used to using it.

 

  1. Can you take this table and visualize the SNAP household growth since 2010?
  2. Can you visualize this data in percentages of total US population? (Use persons) and use 300 MM as overall population.

Screen Shot 2013-09-13 at 9.35.49 PM

Source: http://www.fns.usda.gov/pd/34SNAPmonthly.htm

 

Now take a look at the current unemployment rate of the US in the same time period.

  1. Can you take this table and visualize the decline in unemployment in the US?
  2. Is there a way to combine these two data sets to show a comparison between the two?  What is interesting about this data?

Screen Shot 2013-09-13 at 9.35.56 PM

Chris Lovett

 

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11 thoughts on “BMGT 311: Assignment #4 Data Visualization”

  1. Below is a link to my assignment for Week 4, visualization of data. Question number 4 asks if there is anything interesting about the comparison of data between unemployment trends and SNAP use trends. The answer is yes. When visually represented you can see there are clearly divergent trends happening among these two sets of data. Over time the percent of the U.S. population on SNAP has increased while the percent of unemployed Americans has decreased. This data seems to be logically inconsistent.

    http://www.slideshare.net/ewessing/us-stats-20

  2. Below is the link to my fourth assignment. To answer question four, the answer is yes. When put into graph form, it is noticeable that there are two different trends occurring. As time went on, the percentage of the United States population (households) on SNAP has increased, while the percentage of the United States unemployed population has decreased. Logic would suggest that the greater percentage of population being employed would result in a less percentage needing government food assistance.

    http://www.slideshare.net/gmlohr/genevieve-lohr-us-stats-2010-2013

  3. Below is the link to my fourth assignment. To answer question four, the answer is yes. When put into graph form, it is noticeable that there are two different trends occurring. As time went on, the percentage of the United States population (households) on SNAP has increased, while the percentage of the United States unemployed population has decreased. Logic would suggest that the greater percentage of population being employed would result in a less percentage needing government food assistance.

    http://www.slideshare.net/gmlohr/genevieve-lohr-us-stats-2010-2013-26397446

  4. The answer to number 4 is yes. It is easy to look at a quick glance and not be number specific that you can tell that there has been an increase of households and SNAP since 2010 and then also to see the decline of unemployment since 2010. If you want a quick response it is easier to look at the visualization of information than looking at the numbers and try to decipher it. You will come to the same conclusion, hopefully, but it also might take you longer than it would looking at the visualization. What is interesting about this data, as you can see in the visualization, unemployment as decreased while households on government food assistance has increased. Something isn’t adding up as to why it is happening. I think if I just would’ve looked at the numbers I never would’ve been able to see the rapid difference side to side as you can see in a visualization, because the gap is getting bigger as the years progress, but you can’t really see that by just looking at the numbers. The first thing that you will see is that the pattern is being consistent as either increasing or decreasing, but the increasing gap doesn’t jump out at you as much as it does by looking at the visualization.

    the link to my fourth assignment is below.

    http://www.slideshare.net/kenzietrunzo/us-stats-2010-2013

  5. The answer to number 4 is yes. It is easy to look at a quick glance and not be number specific that you can tell that there has been an increase of households and SNAP since 2010 and then also to see the decline of unemployment since 2010. If you want a quick response it is easier to look at the visualization of information than looking at the numbers and try to decipher it. You will come to the same conclusion, hopefully, but it also might take you longer than it would looking at the visualization. What is interesting about this data, as you can see in the visualization, unemployment as decreased while households on government food assistance has increased. Something isn’t adding up as to why it is happening. I think if I just would’ve looked at the numbers I never would’ve been able to see the rapid difference side to side as you can see in a visualization, because the gap is getting bigger as the years progress, but you can’t really see that by just looking at the numbers. The first thing that you will see is that the pattern is being consistent as either increasing or decreasing, but the increasing gap doesn’t jump out at you as much as it does by looking at the visualization.

    the link to my fourth assignment is below.

    http://www.slideshare.net/kenzietrunzo/us-stats-2010-2013

  6. http://www.slideshare.net/brandonmarsico/presentation3-26398897

    There is a noticeable increase in SNAP households along with a decrease in unemployment. I find that looking at the chart helps visual this anomaly more than it does just by looking at numbers. By putting this data in chart form, it helps create a more emotional impact on the person viewing the data. As for why these trends are happening, could it be that the unemployed are just giving up and brushed off completely?

  7. Below is the link to my fourth assignment. To answer question four, the answer is yes. When put into graph form, it is noticeable that there are two different trends occurring. As time went on, the percentage of the United States population (households) on SNAP has increased, while the percentage of the United States unemployed population has decreased. Logic would suggest that the greater percentage of population being employed would result in a less percentage needing government food assistance.

    http://www.slideshare.net/gmlohr/genevieve-lohr-us-stats-2010-2013-26397446

  8. Hello. Attached is my Slideshare link. My answer to question 4 is Yes you can combine them. You can see the different areas each subject goes in the graph. It’s interesting that as the people in SNAP increase, the unemployment rate declined. I would have thought that as the unemployment rate increased, that the people in the SNAP program would decline. This is just saying that even if people get jobs, they are still using the SNAP program.

    http://www.slideshare.net/marcuswlchristian/marcus-christian-week-4-homework

  9. My presentation is available at: http://www.slideshare.net/nikkischutz/us-unemply.

    While the U.S. unemployment rate and SNAP benefit data can be integrated in such a way as to support an unexpectedly inverse correlation between the two, the data itself isn’t appropriate to draw such a conclusion. SNAP data for persons is accounted for and provided as a percentage of the total U.S. population; unemployment rates, however, are drawn from the U.S. labor force, which comprises slightly more than half of the total U.S. population. A direct comparison of the two skews the proportion of individuals receiving SNAP benefits to greatly exceed the number unemployed, but fails to account for a significant portion of the SNAP group that are either unable to join or have exited from the labor force (e.g., children under 16 and persons receiving disability or social security benefits); thus, a more accurate, though likely still misleading, comparison would examine unemployment rates in connection with the change in number of households receiving SNAP benefits.

    Beyond that, if one were to assume that the numbers are indeed accurate, then the most obvious explanation of the disparity is that more jobs do not necessarily equal good jobs that would allow the income of individuals/households to rise above the poverty level and/or criteria for assistance.

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