Vaccines, Lightning, Lottery: What Are the Odds?

The odds of being killed in a tornado in a given year are 1 in 5,693,092.

The odds of being struck by lightning in a given year are 1 in 1,107,143.

The odds of winning the grand prize in the lottery are 1 in 175,223,510.

Thank you Mr. Lottery!

Why am I mentioning this? Why is it even relevant? Surely almost all of you have been through a tornado and survived, right? Surely every single one of you reading this has seen lightning and are still alive, right? And I am going out on a limb here, but almost certainly none of you reading this has ever won the grand prize of the lottery, correct?

I am bringing these statistics up for one simple reason: vaccines.

Yes, the scary and extremely controversial subject that somehow science doesn’t understand yet we are still pumping our kids full of them. Well, why don’t we look at some data?

Per: National Vaccine Injury Compensation Program (VICP) Adjudication Categories by Vaccine for Claims Filed Calendar Year 2006 to Present.

Vaccine Alleged by Petitioner

No. of Doses Distributed US CY 2006 – CY 2013 (Source: CDC)

Compensable

Compensable Total

Dismissed/ Non-Compensable Total

Grand Total

Concession

Court Decision

Settlement

DT

652,327

1

3

4

4

8

DTaP

75,888,233

10

17

71

98

72

170

DTaP-Hep B-IPV

43,929,797

4

6

18

28

38

66

DTaP-HIB

1,135,474

0

1

1

DTaP-IPV-HIB

39,590,896

5

5

11

16

DTP

04

1

2

3

2

5

DTP-HIB

04

0

1

1

Hep A-Hep B

11,662,755

8

8

1

9

Hep B-HIB

4,796,583

1

1

1

3

1

4

Hepatitis A (Hep A)

124,212,280

2

4

20

26

18

44

Hepatitis B (Hep B)

129,820,136

2

10

35

47

34

81

HIB

83,517,849

1

4

5

4

9

HPV

67,250,524

10

62

71

80

151

Influenza5

944,000,000

36

67

728

831

165

996

IPV

58,019,052

4

4

2

6

Measles

135,660

1

1

1

Meningococcal

58,412,363

1

1

22

24

3

27

MMR

73,441,556

15

13

52

80

69

149

MMR-Varicella

11,028,270

8

7

15

8

23

Nonqualified6

N/A

0

21

21

OPV

0

1

1

3

4

Vaccine Alleged by Petitioner

No. of Doses Distributed US CY 2006 – CY 2013 (Source: CDC)

Compensable

Compensable Total

Dismissed/ Non-Compensable Total

Grand Total

Concession

Court Decision

Settlement

Pneumococcal Conjugate

132,932,107

1

5

6

13

19

Rotavirus

70,719,103

1

3

15

19

6

25

Rubella

422,548

1

1

1

Td

55,742,830

4

5

49

58

15

73

Tdap

155,106,848

11

6

74

91

11

102

TETANUS

3,836,052

3

17

20

10

30

Unspecified7

N/A

1

2

3

541

544

Varicella

90,425,492

3

5

20

28

10

38

Grand Total

2,236,678,735

114

142

1,225

1,480

1,144

2,624

Guys, this is it. This is all of the actual cases taken to court that has found vaccines accountable for an injury. All of them.

I honestly don’t want to hear,”What about the shots that the parents never took the kids to trial over!” That is a terrible argument. If your kid were “vaccine injured” and “regressed to autism,” would you not seek out legal help? There are ambulance chasers plastered over every city that work for free if no money is won, are you telling me they won’t do the same in HUGE money cases like this?

Rant over. What we see here is this: There is a 0.0000013% chance of your kid suffering an injury from a vaccine. You have a 1 in 1,300,000 chance of being injured from vaccines. Sure, you have better chance of being injured by vaccines than winning the lottery and being killed by tornadoes. Lets throw lottery out. Lets look at tornadoes. You are a little less than 5 times more likely to be injured by vaccines than you are to be killed by a tornado. That is not much. Are you fleeing tornado zones in mass exodus? No.

You are MORE likely to be injured in a lightning strike than you are by a vaccine. Do you cry foul and petition to the government to end lightning? No!

The numbers do not lie. They simply do not. If you are against vaccines, you have a 99.9999987% reason to not be. And after that, well, you are simply pleading ignorance.

Expectations and Realities: Week 2 AP Top 25 College Football Teams

Last week I reported how top 25 teams performed relative to their expectations. In that article I compared vegasinsider.com’s lines for the AP top 25 teams to the actual scores for that week’s games. Here is week 2’s comparison.

During the first week of college football, Washington was the only team to drop from the top 25. Louisville replaced them for the 25th spot. Because of this, Washington was not included this week.

In the table below you will find the 25 teams ranked in the AP preseason poll, the predicted spread, the actual result, and the percent error. The teams are sorted based on how well the team performed based on the spread for that game. Teams with a positive percent error performed better than expected while teams with a negative percent error underperformed. Note: this is not a measure if a team won or lost a game, rather a measure of how well the team won or lost the game. For example, Texas A&M was predicted to beat Lamar by 46.5 points but outscored them by 70 points. Texas A&M performed 50% better than predicted.

Relative Performance of Week 2 AP Top 25 College Football Teams

Rank Team Opponent Spread Actual %Error
16 Notre Dame Michigan -4 -31 675%
24 Missouri Toledo -3.5 -25 614%
14 USC Stanford 3 -3 200%
15 Ole MIss Vanderbilt -18.5 -38 105%
23 Clemson South Carolina State -34 -66 94%
4 Oklahoma Tulsa -24.5 -45 84%
12 LSU Sam Houston State -32 -56 75%
9 Texas A&M Lamar -46.5 -70 51%
17 Arizona State New Mexico -24.5 -35 43%
3 Oregon Michigan State -13.5 -19 41%
10 Baylor Northwestern State -46.5 -64 38%
5 Auburn San Jose State -34 -46 35%
25 Louisville Murray State -35.5 -45 27%
6 Georgia Bye 0 0 0%
2 Alabama Florida Atlantic -42 -41 -2%
18 Wisconsin Western Illinois -41 -34 -17%
21 South Carolina East Carolina -14.5 -10 -31%
7 Michigan State Oregon 13.5 19 -41%
1 Florida State Citadel -56.5 -25 -56%
20 Kansas State Iowa State -12 -4 -67%
11 UCLA Memphis -22.5 -7 -69%
22 North Carolina San Diego State -14.5 -4 -72%
19 Nebraska McNeese State -35.5 -7 -80%
13 Stanford USC -3 3 -200%
8 Ohio State Virginia Tech -10 14 -240%

Use the following chart to help visualize the data in the table.

Many teams played easy opponents during week 2 as you can tell by the number of 30+ point spreads. However, there were some games that were predicted to be close. The most surprising win this week, for a top 25 team, comes from Notre Dame’s 31-0 shutout over Michigan. Notre Dame was favored by 4 points. This indicates that it was expected to be a close game that instead resulted in a blowout.

The first 14 teams in the table exceeded expectations while the bottom 11 underperformed.The top 3 overachievers this week were Notre Dame (675%), Missouri (614%), and USC (200%). The top 3 underperformers this week were Ohio State (-240%), Stanford (-200%), and Nebraska (-80%).

 

Important notes:

1. Spreads can be found at vegasinsider.com.

2. Percent error is calculated as

3. I understand that spreads are typically used for gambling purposes and that the lines move. However, it is important for the spreads to reasonably accurate in order for the house or bookie to make money. Lines are a consistent source of weekly predictions

How Good is Cam Newton?

Cam Newton is an overall number 1 pick, and he now can add quarterback of a playoff team to his resume’. Newton is already being credited for the Panthers’ 2013 success where they finished 12-4.  In this same season, Newton is credited for his increase in productivity compared to the year before. This is how it goes in football. QBs get all the chicks but also lose the chicks when the team play suffers.

When the Panthers were disappointing the previous years, all you heard were stories about his immaturity and how he doesn’t take the game seriously. Fast forward one incredible defensive season later, Cam is now the next Tom Brady and about to ring off a series of Super Bowl wins. The narrative changes with team very quickly.

Cam Newton training with Chris Weinke at IMG Academy

Superstar? The numbers say average.

I personally found that the turnaround had more to do with the Panther’s incredible defense. Per Football Outsiders, the Panthers defense ranked 3rd in DVOA. DVOA, in this instance, measures just how good a defense is on a per play basis. The Panthers ranked 3rd allowing -18.0% less value per play than the average team. The Seahawks were number one with a legendary DVOA of -30.0%. While the Panthers weren’t the Seahawks, they were pretty damn good. The Panthers were the number 1 overall pass defense on DVOA, even better than the vaunted Seahawks. When we are talking about a clear top 3 defense, you are going to win games.

Carolina Panthers defense tackles RB Alfred Morris (46).

Here are the real superstars of the Panthers.

Back to Cam Newton. How much of a help was he in obtaining this 12-4 turnaround? And how does he stack up against others? Lets have a look shall we.

Defense-Adjusted Yards Above Replacement

DYAR tells us exactly that. How many yards, adjusted for defense, is a QB worth over a league average replacement. Newton places a very pedestrian 17th with a DYAR of 421. It definitely speaks well that he is an above average player, but at a 17 ranking, he seems to be only that, slightly above average. Andy Dalton and Carson Palmer are just ahead of Newton in these rankings. Hardly superstar status (although Cincy feels the need to pay Dalton like he is one).

Andy Dalton

To say Dalton didn’t deserve his contract is an understatement.

Defense-Adjusted Value Over Average

DVOA represents a per play measurement of how good a QB is over an average QB in the same situation. Newton actually falls back a little bit to a 19 ranking with a small 1.7% more value than an average player. Again, above average but ever so slightly. These rankings put Newton behind Josh McCown and in a league with Dalton, Palmer, and Ryan Fitzpatrick. If we are giving Cam credit, the credit seems to be vastly overstated.

Cam Newton

Cam needs to hone his passing skills.

Cam’s Passing

Cam Newton training with Chris Weinke at IMG Academy

Having seen Cam’s passing numbers, he honestly looks like a very league average QB. However, he does do some extras to bump up his passing value and overall value (which we will get to). He had a very strong 24TDs to only 13 INTs. That’s a positive ratio that is more indicative of a top 10 QB. He needs to throw more TDs, but as long as his INTs are down, it’s a major plus.

At this point, Newton probably sits as the 15th best passer in the league. I would place Andy Dalton ahead of him, but Palmer and Fitzpatrick don’t quite bring his low INT rate skill. C+ passing grade.

Cam’s Running

Now here is where Cam shines a little bit more. Cam has a DYAR of 102 for a rank of 5th. No matter how you slice it, picking up extra yards on the ground is a valuable skill and he excels at it. His DVOA falls to 24th, however, that is a case of him taking off too much. He can get the yards, but he needs to reel it back in from time to time and make sure each play is getting maximum value. Newton had 6 TDs running it, which is a huge plus. He also had 2 fumbles, but that is to be expected. Still a nice ratio of scoring to turnovers.

Newton is a good runner. I would give his rushing a B+.

Cam Newton Jersey

So Where Does He Sit?

Cam Newton is no superstar, and he had minimal to do with the Panthers turnaround. He shouldn’t receive the praise and credit, but that doesn’t mean he doesn’t bring value. Overall, I would say Cam Newton is somewhere between the 12th and 16th best QB in the league. He is good but only slightly good. You see a lot of positives in his game and you hope that he continues to grow.

But please, hold the superstar praise for when he actually deserves it.

Are You Really the Luckiest Woman in the World?

I see it every single day. Someone gets a pretty sweet gift and proclaims, “I am the luckiest woman in the world for getting gift x!!!” Sure, we are elated to get gifts and surprises and may be slightly hyperbolic when we get these things. But is there any truth to the claims? I have decided to put some of these claims under the scrutiny of data and see if you really have a claim to being the luckiest woman in the world.

(Please keep in mind this is a tongue-in-cheek piece. I am sure everything about you is simply splendid. Do your thing, girl.)

Claim: I am the luckiest woman in the world to have such a great job.

Doctor Claire

According to Forbes, the happiest job for a woman (factoring in salary, job growth, and job satisfaction) is a diagnostic medical doctor. The median income for this job is $121,000 and has an estimated job growth of 27% through 2020. Pretty sweet gig.

So how many women are doctors? There are approximately 202,000 female doctors in the United States. Out of those, only 11,000 earn in the top 10% ($233,000) of doctors. These salaries are based off of a general practitioner.

Conclusion: Unless you are a doctor earning in excess of $233,000, you do not have a valid claim.

Claim: I am the luckiest woman in the world because my kids are so amazing.

Gregory Smith could read by 2, enrolled in college by 10, is a children’s rights activist, and was nominated for a Nobel Peace Prize at the tender age of 12.

Michael Kearney graduated college at 10, was a teacher at age 17, spoke his first words at 4 months, was once the youngest post graduate, diagnosed his own ear infection at the age of six months, and is a millionaire.

Alexis Martin was one of the youngest people to ever be accepted into Mensa, at the age of 3. She has the same IQ as Stepehn Hawking and Albert Einstein.

And just for good measure, literally everyone on this list:

http://www.thebestschools.org/features/worlds-50-smartest-teenagers/

Conclusion: Are one of these kids yours? Claim invalid.

Claim: I am the luckiest woman in the world because I am married to the most handsome man  in the world.

Omar Borkan Al Gala was deported from his country because he was so handsome, officials thought he would give women immoral thoughts. Hold on, I am going to re-type something: HE WAS DEPORTED FROM A COUNTRY FOR BEING TOO FUCKING HOT.

Ok, just wanted everyone to be clear on that.

Conclusion: Your husband is not Omar Borkan Al Gala

Omar Borkan Al Gala...Deported From Saudi Arabia 4 Being To Handsome (Panties Drop)

Claim: I am the luckiest woman in the world because my husband is the smartest man alive

This is easy. Is your husband Stephen Hawking (160 IQ), Christopher Langan (205) , Kim Ung-Yong (210), Paul Allen (170), Rick Rosner (192), Gary Kasparov (190), Andrew Wiles (170), Judit Polgar (for you ladies who love the ladies, 170), Christopher Hirata (225), Terrance Tao (230), or Evangelos Katsioulis (198)?

Only 0.5% of the population have an IQ over 140.

Conclusion: Probably not.

Claim: I got diamonds. I am the luckiest woman in the world.

In 1905 a man named Frederick Wells discovered a rough diamond that was 3,106 carats. Named the Cullinan, it was later cut into 100 smaller diamonds. The largest of those being 530 carats.

Actual-size replica of Cullinan Diamond.

Actual size replica of the Cullinan

In 2012, the Taj Mahal diamond sold for 8.8 million dollars.

The Elizabeth Taylor Diamond sold for $265,697 per carat and 8.8 million for the whole stone.

The total amount that Elizabeth Taylor jewelry collection sold for was 137.2 million dollars.

Conclusion: You do not have any of these diamonds.

Regardless of what I say, having happiness and love makes all of us the luckiest people on earth.

Expectations and Realities: Week 1 AP Top 25 College Football Teams

Week 1 of college football has come and gone. While we wait for the polls to update, let us take a moment and see how each of the teams in the AP top 25 poll performed relative to their predictions.

In the table below you will find the 25 teams ranked in the AP preseason poll, the predicted spread, the actual result, and the percent error. The teams are sorted based on how well the team performed based on the spread for that game. Teams with a positive percent error performed better than expected while teams with a negative percent error underperformed. Note: this is not a measure of if a team won or lost a game, rather a measure of how well the team won or lost the game. For example, Oregon beat South Dakota 62-13. Oregon won their game in convincing fashion. However, Oregon was expecting to win by 54 points, but won by 49 points.

Relative Performance of AP Top 25 College Football Teams

Rank Team Opponent Spread Actual %Error
21 Texas A&M South Carolina 10 -24 340.0%
12 Georgia Clemson -9.5 -24 152.6%
22 Nebraska Florida Atlantic -20 -48 140.0%
18 Ole Miss Boise State -10 -22 120.0%
15 USC Fresno State -18.5 -39 110.8%
17 Notre Dame Rice -19.5 -31 59.0%
6 Auburn Arkansas -17 -24 41.2%
10 Baylor Southern Methodist -33 -45 36.4%
5 Ohio State Navy -13.5 -17 25.9%
13 LSU Wisconsin -3.5 -4 14.3%
8 Michigan State Jacksonville State -34.5 -38 10.1%
11 Stanford UC Davis -42.5 -45 5.9%
4 Oklahoma LA Tech -33.5 -32 -4.5%
20 Kansas State Stephen F. Austin -42 -39 -7.1%
3 Oregon South Dakota -53.5 -49 -8.4%
23 North Carolina Liberty -31 -27 -12.9%
14 Wisconsin LSU 3.5 4 -14.3%
24 Missouri South Dakota State -25.5 -20 -21.6%
19 Arizona State Weber State -46 -31 -32.6%
2 Alabama West VA -23 -10 -56.5%
7 UCLA Virginia -19 -8 -57.9%
1 Florida State Oklahoma State -20.5 -6 -70.7%
25 Washington Hawaii -17.5 -1 -94.3%
16 Clemson Georgia 9.5 24 -152.6%
9 South Carolina Texas A&M -10 24 -340.0%

I’ve added the following chart to help you visualize the data.

The first 12 teams in the table exceeded expectations while the bottom 13 underperformed. Texas A&M, ranked 21, tops the table exceeding predictions by 340% outscoring number 9 South Carolina 52-28. Expectedly, South Carolina underperformed by 340%. Defending national champions Florida State struggled in their opener underperforming by 70.7% against Oklahoma State. Georgia/Clemson and LSU/Wisconsin games were other notable games as it marks the only other two Ranked teams that lost their opener. The Georgia/Clemson game had an error of 152.6% while the LSU/Wisconsin game had an error of 14.3%. While Georgia trumped Clemson in a 2nd half shut out, LSU rallied in the second half to edge out their spread by half a point against Wisconsin.

On average, the ACC underperformed by 78.8% while the SEC exceeded expectations by an average of 31.3%. Below are the conference averages.

ACC          -78.8%

PAC 12     -12.8%

Big 10       18.0%

Big 12       30.1%

SEC           31.3%

IND           59.0%

Important notes:

1. Spreads can be found at vegasinsider.com.

2. Percent error is calculated as (Spread-Actual)/Abs(Spread)

3. If you like what you see here (or don’t) let me know below. You can also point out mistakes or criticize the article.

Apollo’s Preseason College Football Predictions

SEC Championship Game: #3 Alabama 11-1 (24) vs. #5 UGA 11-1 (17)

Big Ten Championship Game: #1 Michigan State 12-0 (32) vs. #14 Wisconsin 10-2 (10)

ACC Championship Game: #4 Florida State 11-1 (38) vs. #19 Miami 9-3 (15)

PAC-12 Championship Game: #2 Oregon 11-1 (34) vs. #9 UCLA 10-2 (28)

Big XII Champions: #6 Baylor 11-1

College Football Playoffs Seeding

#1 Michigan State vs #4 Florida State

#2 Oregon vs. #3 Alabama

 

Heisman Trophy

Todd Gurley (Winner)

Marcus Mariota

Kenny Hill

Jameis Winston

Bryce Petty


Coach of the Year

http://i0.wp.com/media.247sports.com/Uploads/Assets/431/867/6_2867431.jpg?w=550

Biggest Surprises

Texas Longhorns, Penn State Nittany Lions, and Texas A&M Aggies

Biggest Disappointments

Clemson Tigers, South Carolina Gamecocks, USC Trojans

The Truth about Immigration

Immigrants bring more crime. Wrong. Native-born American men between 18-39 are five times more likely to be incarcerated than immigrants in the same demographic. Numerous reputable studies have shown that the problem of crime in the United States is not caused or even aggravated by immigrants, regardless of their legal status.

Immigrants are taking our jobs. Wrong. CNN reports that immigrants are twice as likely to start businesses as U.S.-born citizens and that immigrants create 28% of all new businesses. Moreover, some immigrants work jobs Americans simply do not want. They are farm workers, janitors, chambermaids, busboys, dishwashers, gardeners, nannies, and household domestics. Those are not the careers most Americans seek. The “good jobs” they do “steal” are just because they’re better in that fieldnot because they’re immigrants (see below).

We need to secure the border first before tackling immigration reform.  Well for starters, the net migration from Mexico has practically fallen to zero. The federal government has spent more money on immigration enforcement ($18 billion) than they have on FBI, Secret Service, Drug Enforcement Administration, U.S. Marshalls, and the Bureau of Alcohol, Tobacco, Firearms and Explosives combined ($14.4 million). The government also spends about 15 times more on immigration enforcement than it did in the mid-1980s, adjusted for inflation. There are more than 20,000 border patrol agents stationed along the border now. So the border is quite secure right now. Lastly, roughly 40% of undocumented immigrants enter the US legally and overstay their visas.

America doesn’t want immigrants here. Well, quite the contrary, most Americans don’t want to kick them all out. In a Fox News Poll, it showed that 74% of the people they polled were in favor of allowing the 11 million illegal immigrant currently in the country to remain in the country and eventually years down the road qualify for U.S. citizenship, as long as they meet certain requirements like paying back taxes, learning English, and passing a background check.

Obama is giving the country to the illegal immigrants. This could be challenged. The Obama Administration has deported as many illegal immigrants in one term as the Bush Administration did in two. In fact, Obama is on track to deport more people than the US did from 1892-1997. As stated earlier, the Obama Administration has put many resources in stopping illegals.

Illegal aliens don’t contribute to the U.S. economy and they don’t pay taxes. I’m pretty sure everybody in this country pays taxes when they purchase anything. Most undocumented immigrants live in Texas and Florida. Neither state has a state income tax. When it comes to federal income tax—well, I believe we should be more concerned about the $305 billion revenue lost due to tax evasion for current US citizens.

Immigrants don’t contribute anything to the country. Currently, one in six college-educated adults in the US was born abroad. There are roughly 35 million immigrants ages 25 and older in America. Of those, 28% had a bachelor’s degree or higher (compared to 29% of American adults 25 and older). Immigrants represent nearly 28% of physicians, more than 31% of computer programmers, and over 47% of medical scientists.

The Truth. We need immigration reform YESTERDAY! This country was founded upon immigration. Keep the American vision alive by demanding that we become the Land of Opportunity again!

The Truth About Your Ice Bucket Challenge Donations

If you are reading this, you have probably heard of the ice bucket challenge.  In short, you get nominated to take the ice bucket challenge.  Once nominated you have two options that you are supposed to choose: either donate $100 to the Amyotrophic Lateral Sclerosis Association (ALSA) or pour a bucket of ice water over your head, donate $10 to the ALSA, and nominate three more people to take the ice bucket challenge.  “Amyotrophic lateral sclerosis (ALS), often referred to as Lou Gehrig’s Disease, is a progressive neurodegenerative disease that affects nerve cells in the brain and the spinal cord.”  It is a terrible disease that ultimately results in death. Donating money to this charity sounds like a good cause.

There are some critics. There are articles and videos that claim ALSA does not spend the money correctly.  After coming across this dissent, I became curious and decided to investigate.  How does the ALSA spend their money and is that spending appropriated correctly? Let us find out.

In this video the author says that less than 8% of the 2012 ALSA expenses went to research.  The 2012 ALSA annual report (see page 12) confirms this claim.  In the table below we can see that 7.71% of ALSA expenses went towards research.  I found it interesting that the consolidated financial summary is accompanied by this comment “The consolidated summary has not been audited or reviewed by the auditors and is not part of their financial reports.” and decided to investigate.  After investigating, I found a discrepancy.  The consolidated financial summary reports a “total combined revenue” of $55,446,772 but the total expenses for 2012 is reported as $15,435,227.  I could not reconcile the numbers in this report.  Feel free to comment if you reconcile the numbers.

Using the expenses for 2012, we see an entirely different situation.  ALSA spent $3,904,240, or 25.3% of their 2012 expenses on research.  In addition, ALSA spent $4,629,111 or 30.0% on patient and community services, $1,859,100 or 12% on public and professional education and $3,269,624 or on fundraising.  In 2012, ALSA spent a total of $13,662,075 or 88.5% of their expenses on research, fundraising, or ALS awareness leaving 11.5% for overhead. Put another way, in 2012 88 cents out of every dollar spent by ALSA went to better understanding ALS.

We find a similar trend for the 2013 year.  In 2013 the ALSA had an expense total of $25,737,701, 66.7% more than in 2012.  Of the $25,737,701, ALSA spent $6,616,367, 25.7%, on research.  While ALSA proportionally spent similar amounts of research, the total dollar amount spent on research increased in 2013.  Additionally, 91.5% of ALSA spending in 2013 went towards research, fundraising or ALS awareness leaving only 8.5% for overhead.

The trend continues for the year ending in 2014.  In 2014 the ALSA had an expense total of $26,204,122.  Of this, ALSA spent $7,170,481, 27.4%, on research.  The ALSA spent 1.7% more in 2014 on research.  Additionally, 92.7% of ALSA spending in 2014 went towards research, fundraising or ALS awareness leaving only 7.3% for overhead.

Of course this doesn’t even begin to address money and awareness raised by the ice bucket challenge.  The ALSA has raised $79.7 million  as of August 25th.  You can rest assured knowing that, for the most part, your donations are being put to good use.  But don’t just take my word for it.  The ALSA meets all the Better Business Bureau’s 20 standards for charity accountability.  In addition Charity Navigator gives them a 4 star rating.

patrick-stewart-ice-bucket-challenge

Education and Race: By the Numbers

Since the hot topic of the day has been race, I wanted to look at race in a way that was not the normal rhetoric. I wanted to look at something we could absolutely quantify. You cannot quantify opinions or morals because they differ and hold different values for different people. If I was going to write about race, I wanted an unbiased look into it. I wanted to come with facts and stats instead of emotion. Maybe hard data can move the conversation in a positive way, or maybe it will fall by the wayside. I am not here to change the world, I am just here to present facts so that others may go forth and maybe be the change that they want.

As you may have inferred by the title, we are looking at education here. I wanted to look at who was graduating, what their grades were, and where the money was coming from. Before looking at the data, the first thing you will notice is that white people are going to college at a much higher overall number than any other race. But I also want to see what the true rates are. You could have 1 million people in college, but if that number is out of 1 billion (exaggerated for example), that is absolutely a lower rate than 100,000 out of 1 million.

So, without too much babbling on, lets take a look at our first set of data.

Note: All data is from 2010-2011

Degrees awarded by Race

Here is a look at degrees awarded by race, per Institute of Educational Sciences.

Race
Total Number
Percent Distribution
White
552,863
66.3%
Black
113,905
13.7%
Hispanic
112,211
13.5%
Asian/Pacific Islander
44,021
5.3%
American Indian/Alaskan Native
10,337
1.2%

 

We obviously see that white people earned degrees at a an overall total number that is much higher than all other races…combined. My first question will spawn the rest of the data lines we look at. That question is: is this a case of white people having much more access to education or is it a case of there being a large amount of white people? Lets look at the total population that year, per US Census Bureau:

  • White – 223,553,265 people, or 72.4% of the population.
  • Black- 38,929,319, or 12.6 % of the population.
  • American Indian or Alaskan Native – 2,932,248, or 0.9% of the population
  • Asian/Pacific Islander – 15,214,265, or 5.0% of the population.
  • Hispanic – 35,305,818, or 12.5 % of the population.

Comparing population to degrees earned, we can see that Black, Asian/Islander, and American Indian are all earning degrees at a higher percentage than what their total population percentage is. That’s a good thing. White and Hispanic people are earning degrees at a lower percentage than their overall percentage of the population, not as good for them.

We can’t say too much from this info. But it does give us a little bit clearer of a picture on how races are graduating comparatively. With the exception of White, we are graduating races from college at a congruent rate to their population percentage. In the case of white people, their college graduation rates are much below that of other races, when also factoring in total population.

Where is the Money Coming From?

The first data set I want to take a look at is private scholarship funding, per finaid.org.

We are done looking at total number now. I want to look at rates, as we have already seen what population totals are. We know there are a lot of whites, and other races are the monitory. So overall numbers just skew the real data. We want rates as they reflect the real data in a better light. Saying whites get 100 million in funding compared to 10 million for blacks just isn’t a fair number to throw out at this point. Anyways, one the the data.

Race
% Receiving Private Scholarship (of all enrolled students)
Average Amount Received
% of Scholarship Recipients (of total scholarships for all races)
% of Total Funding
% of Student Population
White
6.2%
$2,368
69.3
65.0%
61.8%
Black
4.4%
$2,671
11.2%
11.9%
14.0%
Hispanic
3.5%
$2,269
9.0%
8.1%
14.1%
Asian/Pacific Islander
8.4%
$4,001
5.1%
7.5%
6.6%
American Indian/Alaskan Native
10.8%
$2,935
1.6%
1.9%
0.7%

 

If we refer back to the general population statistics, we can see that the Black students receiving private funding is fairly congruent with overall population. The real winners in private scholarships are American Indians and Asians. They receive a much higher percentage of scholarships (in relation to population) and Asians have access to a significant amount more money on an average scholarship amount basis. Again, the White population sees a large dip across that board. But we need to look at 2 other forms of funding, Pell Grant and Academic Scholarships. Onto the Pell Grants!

Honestly, looking at Pell Grants is sort of an exercise in the obvious, as they are set up for low income and minority students. Minority students receive a very high proportion of these funds, and are the obvious winner in this funding.

 

Race
% of Total Pell Grant Recipients
% of total Pell Grant Funding
White
46.3%
44.2%
Black
23.7%
24.0%
Asian/Pacific Islander
5.5%
6.2%
Hispanic
20.4%
21.5%
American Indian
1.1%
1.1%

The Black and Hispanic population see a huge benefit from Pell Grants. And when we take population into account, that benefit is even greater as they are receiving a ratio of funds way above their ratio of population. Again, White people have way less access to and receive way less funds than minorities. This really comes as to no surprise, as Pell Grants were not really set up to benefit the majority.

Institution Granted Academic Scholarships

This is simply an academic scholarship based on merit. If you make good grades, research, and many other things, you can receive a merit based scholarship. We are going to look at GPA of college students by race. This will give us a good idea if these merit based scholarships are being handed out based on…well, merit.

Race
0.5-0.9 GPA
1.0-1.4 GPA
1.5-1.9 GPA
2.0-2.4 GPA
2.5-2.9 GPA
3.0-3.4 GPA
3.5-4.0 GPA
White
0.9%
2.8%
4.3%
11.7%
17.8%
26.2%
36.3%
Black
2.0%
5.1%
8.2%
18.0%
22.1%
23.5%
21.0%
Hispanic
1.3%
4.2%
7.0%
15.3%
21.1%
25.4%
25.6%
Asian/Pacific Islander
0.7%
2.8%
4.1%
12.1%
19.0%
26.0%
35.3%
American Indian
1.2%
4.1%
10.2%
13.7%
25.8%
20.4%
24.6%
As we can see from this chart, Whites and Asians are more likely to have higher GPAs when compared to other minorities. Looking at this data, we should be able to infer that White and Asian college student populations have access to more merit based funding. Lets look at that data.
Race
% Receiving Merit Based Funding (out of all students sorted by race)
% Receiving Merit Based Funding (out of all races receiving merit based funding)
% of total Merit Based Funding
% of Student Population (out of all races)
White
10.7%
75.5%
75.9%
61.8%
Black
5.9%
9.3%
9.1%
14.0%
Hispanic
4.8%
7.7%
7.0%
14.1%
Asian/Pacific Islander
5.8%
3.9%
4.8%
6.6%
American Indian
7.0%
0.7%
0.5%
0.8%

This is where I noticed the most discrepancy, and it is huge. White people have access to far more merit based funding than any other race. Even above the population ratio. But who has the biggest gripe? Asians. They have grades congruent or above that of the White population, so one would expect them to show a higher ratio in merit based funding. The other races really have no gripe in this issue, as the grades aren’t as high as White and Asian populations.

What to Make of This Data

We cannot make sweeping conclusions about race and higher education, but we do see some patterns.

  • The Asian population absolutely has the largest reason to complain and it is not even close. Asians should receive merit-based funding at a much higher ratio. They make the grades and get less recognition for it. The other races received a lower ratio of merit based funding, but their grades were consistently lower.
  • When looking at ratios of students and population, Black, American Indian, and Asians all have graduation rates at or above normal population ratios.
  • White and Hispanic populations show consistently lower ratios of graduation and ability to obtain funds (outside of Merit based funding for White people) than that of their general population ratios.

There are way more factors and numbers we can look at, but the data presented here are major factors in education. I think we can actually take these numbers and make generalized statements, and then go from there but digging into deeper subsets of data.

 

Despite the highest population, White people graduate less people and have an access to a lower rate of funds than their minority counterparts. However, White people make better grades than all of their minority counter  parts, save for Asians.
The Black population graduates people at a higher rate than their general population ratio. The Black population also has access to a higher ratio of funds, when compared to general population.
Asians have a legitimate gripe. Despite grades slightly above Whites, they have way less access to merit based funding. Asians also graduate a at a higher ration than the general population accounts for.
American Indians have a higher ratio of access and funding than their ratio of population. Across the board. I don’t know why this is, but obviously they are doing something.
Final Thoughts
Like I said, I wanted to present hard data, and there is much more data than what is here, but the conversation has to be started somewhere. You can’t argue that when looking at population, minorities have a better graduation rate and an easier access to funds that pay for college. White people also make better grades, and are rewarded as such. However, the White population doesn’t get the opportunity outside of school that others do, and when in school, seem to either fly or fall face first with little in between. Asians have the real discrimination when we look at everything. They are the one population has an obvious disadvantage in these data sets. But that is only one category, as they excel in everything else.
The big question is, what does this mean? I guess the data is for you to decide and do what you want with.
RaceEducation

4 Ways to Keep a Pay Raise from Stealing Your Joy

Salary increases are very important to self-esteem and motivation.  However, joy is much more important.  Often times, salary increases can steal your joy—making you wish you had your old salary back.  As a by-product of this bittersweet phenomenon myself, I have several tips that you and the folks you share this article with can use to maintain joy or increase joy throughout your careers.  (Please follow the chart below as a reference guide)

Job Happiness

(1) Seek Promotions or Lateral Moves Within Current Company

This tends to be easier at larger firms; however, smaller firms may give this opportunity as well.  In an ideal world, I would have done this at the first company that I worked for after college.  The company provided a large network for career paths at the location I was stationed as well as at other locations in the region.  In fact, this type of mobility and versatility was encouraged by management (to a point).  As stated in the title of this section, sometimes you do not necessarily need a pay increase or promotion to increase your joy, you just want a change of scenery. Staying with the same company makes that possibility quite easy—as long as you like the company you are with, of course.

(2) Keep Current Job and Develop a “Side Hustle”

What if you have very predictable working hours and lots of leisure time, but the pay is awful?  That’s how I felt within Firm B in 2012.  Nothing got on my nerves more than knowing that the peers I graduated with were making more money that I was.  However, instead of being smart, my pride got the best of me—I wanted employment elsewhere.  With the amount of leisure time that I had though, getting a new job should have been the last thing I wanted to do.  I should have sought a side hustle.  A side hustle is a miniature version of the DREAM CAREER that you want in the future.  If you work 40 hours per week or less, I highly recommend this option for increasing or maintaining joy.  Use your spare time to make your dreams come true—maximizing your joy and your checking account.

(3) Reduce Personal Debt and Give Yourself a Raise

Simply put, if you eliminate your debts (student loans, car loans, credit cards, etc), you will effectively have more recreational money and investment money—you have given yourself a raise!  Not only does this mean that you have more money to have fun with, but you also have more money to invest in yourself and your family (please revisit Step 2).  Reducing your debts is completely within your control as well.  So unlike landing a promotion or snagging a raise, you do not have to depend on luck—you can depend on faith and will-power! What’s not joyous about that?!

(4) Thoroughly Vet Opportunities for Advancement before Jumping Ship

The grass isn’t always greener on the other side.  You heard me earlier mention how I had almost laughably easy working hours.  I haven’t had that type of work/life balance in years.  And the stress is definitely wearing me down.  However, this could have all been avoided if I vetted the companies that I wanted to work for as thoroughly as possible.  Sometimes this isn’t easy, but it can be done.  Ask people who currently work at the firm that you wish to apply for.  If you end up getting an interview, ask to speak to an individual who has a similar job to the one you are applying for.  And lastly, if you get some unescorted time, look for the people who have the worst jobs within sight—they might be the most honest with you! If you get “bad vibes” after doing a proper vetting, then stay put and wait for another opportunity to arise—a pay increase isn’t worth sacrificing your joy for!

#CareerJoy What are some other ways to maintain joy while also increasing your income?