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Redesign Project

 

Youth Indicators, 2005

Trend in the Well-being of American Youth

 

By Ji Woong Oh

 

Beginning

 

At first, I was trying to= find some poorly represented data from financial companies and websites, but aft= er spending several hours, I realized that nowadays they use most up to date programs to represent their data, so I gave up on my initial interested are= a, and started to google.

 

Education is my other are= a of interest (my mother is a current elementary teacher), and from the U.S. Department of Education, I finally found some graph I can improve, or repre= sent in different ways.

 

 

Redesign

 

Source:=

http://nces.ed.gov/programs/youthindicators/Indicators.asp?PubP= ageNumber=3D32

 

3D"Median

 

This graph doesn’t look too bad, compared to others I = have seen, but I could see I could apply some of the techniques I learned in cla= ss, and I decided to go on with this graph.

 

This graph shows the interested readers the income in the U.S. earned by both male and female, with different age group.

It is quite clear from the graph that the differences in ear= ning income between male and female has been reduced significantly, especially f= or the younger sector of the age.

 

This might tell the readers that education in the U.S. has been quite effective and equally taught without much sexual disadvantage (as this data is from the U.S. Education Department)

 

 The purpose of= this data or this graph was to show readers that inequality of earnings in sex is continuously disappearing.

 

I did two redesigns, simply because I wanted to use different techniques to show different ways to present the data.

 

First redesig= n

 

 

In the first redesign, I did not mark each data points as I = did in the second one because I thought that the purpose of this graph was not about actual data, but what it tells us, so I did reproduce the graph myself with R, but I included the differences of the male and female data in the second panel of the graph.

 

The second panel of the graph is somewhat interesting.  This clearly shows how much more m= en have been making than women throughout the years.   The reason I included the se= cond panel is to show the actual amount of difference over time. 

 

In the original graph, it looks like there has been signific= ant decrease in gap between earnings in male and female, since the amount of earnings has been increased over years.&nb= sp; But the second panel of the redesign graph shows us that the dollar amount difference in 2002 is pretty much same as 1955.   Of course, male made signifi= cantly more than female during mid 60’s to mid 80’s but I see this as = war effects. 

In fact, the gap between male and female in age group 20 to = 24 has been increased after 1995.

 

Considering the fact that this numbers are all inflation adjusted, plus the change in living standard and lifestyle, American still = have long way to go in terms of education in gender.

 

Second Redesign

 

In the second redesign, I just made look better and clearer = with using distinct color and notations on the data points.

 

I use circle for the male data points and triangle for femal= e, but used dashed line and empty figures for the data points represent age gr= oup 20 to 24.

Also, I used manly color for male and girly color for female= to distinguish more clearly.

 

 

End

 

What I like to do more on this graph is to use interac= tive tool for this graph. For example, it would be nice to show actual data numb= ers and selective year when reader points at them.  Also I like to link each data poin= t with extra facts about that specific year, such as the fact about what was the m= ost famous and highly valued jobs, or how well the economy was, or any historic significance in that particular time of period.

 

Source:=

&n= bsp;

http://nces.ed.gov/programs/youthindicators/Indicators.asp?PubP= ageNumber=3D32

&n= bsp;

&n= bsp;

&n= bsp;

&n= bsp;

Additional data

&n= bsp;

Year

All ages, 15 and over (M)

ages 20 to 24 (M)=

All ages, 15 and over (F)

ages 20 to 24 (F)=

1= 955

28,502

22,145

18,352

18,581

1= 960

33,032

23,800

20,032

19,175

1= 965

37,002

26,876

22,176

21,205

1= 970

43,174

31,154

25,447

22,878

1= 975

43,307

28,925

24,777

21,566

1= 980

42,574

26,924

24,883

20,597

1= 985

41,983

23,061

26,607

19,617

1= 990

39,162

22,029

27,663

19,724

1= 991

39,293

20,606

27,383

19,419

1= 992

39,337

20,706

27,683

19,499

1= 994

37,778

19,679

27,304

18,633

1= 995

37,301

20,110

27,208

18,458

1= 996

37,109

20,477

27,629

18,570

1= 997

38,138

20,732

28,451

18,683

1= 998

39,508

22,193

28,892

19,690

1= 999

39,876

21,941

28,886

19,888

2= 000

39,645

22,198

29,206

20,428

2= 001

39,655

21,984

30,154

20,589

2= 002

39,830

21,829

30,363

20,017

&n= bsp;

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