Archive for the ‘decimals’ Category

Math Joke 3:How long will it take you to grow a really bad 70s-styles haircut?

February 18, 2019

The follicle diagram (above) came from bgoffforensics blog. More on hair growth rates here.

QUESTION 1:

How long to grow that really bad 70s style hair cut?

The length of Fabio’s hair (below) is approx 50cm.

t = 50/1.25 months

t=40 months

t = 3 Years 4 months!!!!

Is it worth the effort? Ha!

QUESTION 2:

The growth rates of 1.25 cm/month or 0.5 inches/month are rounded off. Calculations using these growth rates will produce different answers for very large numbers (as above). Read more about the above story in the Daily Mail, UK here. By the way, Asha has been growing her hair for 25 years. Her hair weighs 3 stone or 19 kg. You can find more hair records including the World’s longest ear hair here.

QUESTION 3:

Natasha lives in Rio de Janeiro, Brazil. Read more about Natasha in the Daily Mail here. Once again Mathspig has rounded off the length of hair for easy calculation. The Daily Mail puts Natasha’s ‘mane’ at 5 feet 2 inches or 157 cm. This is the length of hair to be cut off. So Mathspig adjusted the length to 180cm or the approx length of her longest hair.

Posted in %, 10 MATH JOKES, decimals, units length, Year 7 mathspig, Year 9 Mathspig | Tagged %, 1970s, 1980s, calculation, dreads, funny, growth, hair, haircuts, length, Maths, old, rate, ugly, world record, worst | Leave a Comment »

1. You can duck a bullet

January 15, 2019

You will find all the ballistics stats you need here:

Posted in 10 Movie Cliches Debunked with Maths, Arithmetic, decimals, Hollywood Maths, Middle School, units length, units speed, Year 9 Mathspig | Tagged .40 caliber, ballistics, bullet, calculation, Cliche, duck, gun, gun safety, Math, Middle school, movie, pistol, smith & Wesson, speed, velocity | Leave a Comment »

Winter Olympics: Bad Math of Figure Skating Scores

February 22, 2018

According to the fab NBC video, Mathletes, nine Figure Skating judges score competitors for the complexity of each element (eg. Triple axel or triple spin jump) and the quality of the performance producing a score out of ten.

Tessa Virtue and Scott Moir win GOLD at Pyeong Chang 2018

Kailani Craine, Australia

This is a typical figure skating score card for one competitor.

The final score, however, is based on the average for only 5 of these scores. Two are eliminated by random selection (Red Brackets). Then the top and bottom scores are removed and the remaining five scores averaged.

Screen grab NBC Mathletes

……………………………………………………

Now consider the IDENTICAL SCORE CARDS

of Skater A & B:

Skater A:

Four scores are removed. Two by the random selector (in brackets) and then the top and bottom scores (with line drawn through them)

7.00 + 7.00 + 7.00 + 6.75 + 7.00

……………………………………..

= 34.75/ 5 = 6.95

Skater B:

Four scores are removed. Two by the random selector (in brackets) and then the top and bottom scores (with line drawn through them). But this time the random selector eliminates two low scores.

The average:

7.00 + 7.25 + 7.00 + 7.00 + 7.00

……………………………………..

= 35.25/ 5 = 7.05

Same score cards but Skater B gets a higher average score than Skater A.

Skater A is, in fact, beaten by a random number selector!!!!

Posted in decimals, Junior School, Middle School, statistics, Uncategorized, Winter Olympics Maths, Year 7 mathspig, Year 9 Mathspig | Tagged average, Figure skating, how do they, How do they average the score, How do they score, How many judges for, Math, math rules figure skating results, Middle school, Problem, Random Numbers, score, scoring, Why the best figure skater doesn't always win, Winter Olympics | Leave a Comment »

Winter Olympics: Beaten by 0.001 seconds

February 14, 2018

In 2014 Winter Olympics Annette Gerristen (below) lost the Gold Medal in the 1000 m Women’s speed skate competition by 0.02 seconds.

Annette Gerritsen fromthe Netherlands

What are the speed skating times for women?

Women’s Speed Skating Calulations:

Here are the speed calcs for Yara Van Kerkhof of the Netherlands in the 2018 Winter Olympics:

If Yara lost the Gold Medal by 0.02 secs (2 hundredths of a second) what would the distance be between the Gold and Silver place getters?

When 1st and 2nd place are separated by 0.02 seconds, they are travelling at almost the same speed. So the second place contestant is:

23.8 cm behind the Gold Medalist

The 2018 Olympic Gold Medalist in the 500m Women’s Speed Skating was Arianna Fontana.

Italy’s Arianna Fontana wins the 500 m Speed Skating 2018 Olympic Gold Medal in 42.569 seconds ahead of Yara van Kerkhof of the Netherlands and Kim Boutin of Canada.

Men’s Speed Skating:

At longer distances the men’s speed skating speed is similar to the women’s speed above.

If you lose by 0.001 secs…………

Apollo Ono (below) competed in the 1500m men’s speed skating. He has won 8 Olympic Medals.

If a speed skater lost the Gold Medal by 0.001 seconds, the smallest measured time segment at the Olympics, they would be:

1.19 cm

behind the winner. That is less than the length of a small fingernail.

Posted in decimals, Junior School, Middle School, Rates, Sport Maths, units length, units speed, Winter Olympics Maths, Year 7 mathspig, Year 9 Mathspig | Tagged 0.001 secs, 2018, 500 M, Apollo Ono, Arianna Fontana, calculations, How fast are speed skaters?, ice skating, lose, Olympics, pyeong Chang, SKATING, speed, Time, Winter | Leave a Comment »

Cars in the USA are how old? Really? No way! Look at the World and Do the Math

February 3, 2018

The average age of the 60 years of FORD vehicles here is 30 years. MODEL NAMES at end of post.

I did this to show that averages can tell us a lot or, in this case, not very much.

Here are some averages that tell us a lot about different countries and their love of cars!

The average age of vehicles in USA is a record-high of 11.6 years. More here.

Car ownership rates data here.

This is the average vehicle age, which includes vans and utes. Almost 1,000,00 vehicles were scrapped in 2015-16. More than 30% of vehicles are less than five years old. Data here.