Investigate if there is any correlation between the GDP per capita ($) of a country and the life expectancy at birth (years) Essay Example

Investigate if there is any correlation between the GDP per capita ($) of a country and the life expectancy at birth (years) Essay My aim is to investigate if there is any correlation between the GDP per capita ($) of a country and the life expectancy at birth (years). The GDP is the gross domestic product or value of all final goods and services produced within a nation in a given year. GDP dollar ($) estimates are derived from purchasing power parity (PPP) calculations. The GDP per capita ($) shows GDP on a purchasing power parity basis divided by population. The life expectancy at birth shows the average number of years to be lived by a group of people born in the same year, if mortality at each age remains constant in the future. It shows the life expectancy on average for the total population for male and females. Life expectancy at birth is also a measure of overall quality of life in a country and summarizes the mortality at all ages. We will write a custom essay sample on Investigate if there is any correlation between the GDP per capita ($) of a country and the life expectancy at birth (years) specifically for you for only $16.38 $13.9/page Order now We will write a custom essay sample on Investigate if there is any correlation between the GDP per capita ($) of a country and the life expectancy at birth (years) specifically for you FOR ONLY $16.38 $13.9/page Hire Writer We will write a custom essay sample on Investigate if there is any correlation between the GDP per capita ($) of a country and the life expectancy at birth (years) specifically for you FOR ONLY $16.38 $13.9/page Hire Writer The reason for doing this investigation is that I have seen a lot of documentaries and read a lot of articles in the newspaper which have talked about how the gap between rich and poor has increased. This has led to a poorer quality of life in developing countries. So I wanted to see if there was any link between how rich a country is per person and what on average is the life expectancy for a person is in that country. This will help me get a better understanding of how rich a country is how much it affects the quality of life. This is the reason why I think the investigation is worth doing. Data collection: The data I collected was the GDP per capita using the purchasing power parity ($) and the life expectancy at birth (years). I have collected data for these two variables from the whole world. So my population is defined as the whole world. I obtained the data from the www.CIA.gov and clicked on the world fact book. I got 239 pieces of data originally for both then I had to reject 11 pieces of data for both because some countries did not have any data for the GDP. So from the 228 I used a sampling method of choosing every 4th country on the list until I narrowed my sample to 50 countries. I chose every 4th number because when you divide 228 by 50 and choose the integer number you get 4 this ensures this is a random sampled number which provides the most representative sample from the population. I used a systematic sampling method. The list was in alphabetical order and not in rank order for both variables so by using this method Im not creating any bias. Since the data is from the CI A website I must presume that the data is accurate and reliable. Here is a table of my data which has been systematically sampled to show 50 pairs of data: Country GDP per capita, Purchasing Power Parity ($) Life expectancy at birth (years) American Samoa 8000 75.75 Anguilla 8600 76.7 Armenia 3600 66.68 Bahamas, The 15300 65.71 Barbados 15000 71.84 Benin 1100 51.08 Bolivia 2500 64.78 British Virgin Islands 16000 76.06 Burma 1700 55.79 Cameroon 1700 48.05 Central African Republic 1200 41.71 China 4700 72.22 Congo, Democratic Republic of the 600 48.93 Cote dIvoire 1400 42.65 Djibouti 1300 43.13 East Timor 500 65.2 El Salvador 4600 70.62 Ethiopia 700 41.24 French Guiana 14400 76.69 Gambia, The 1800 54.38 Ghana 2000 56.53 Grenada 5000 64.52 Guatemala 3900 65.23 Guinea-Bissau 700 46.97 Honduras 2500 66.65 India 2600 63.62 Iraq 2400 67.81 Jersey 24800 78.93 Kenya 1100 45.22 Korea, South 19600 75.36 Laos 1800 54.3 Liberia 1000 48.15 Macau 18500 81.87 Malaysia 8800 71.67 Malta 17200 78.43 Martinique 10700 78.72 Mayotte 600 60.6 Monaco 27000 79.27 Morocco 3900 70.04 Nauru 5000 61.95 New Caledonia 14000 73.52 Nigeria 900 51.01 Pakistan 2000 62.2 Papua New Guinea 2100 64.19 Philippines 4600 69.29 Reunion 5600 73.43 Saint Helena 2500 77.38 Saint Pierre and Miquelon 11000 78.11 San Marino 34600 81.43 Saudi Arabia 11400 68.73 Modelling procedures: I am going to do a scatter diagram of GDP per capita against life expectancy at birth for my 50 pairs of data to see if there is any correlation. A scatter diagram is an appropriate modeling procedure as it shows a clear relationship between two random variables. As you can see from the scatter diagram the points form a relationship which appears to be a curve so to try to establish a more linear relationship. I am going to do this by first logging my data for the GDP per capita and not logging the life expectancy data and then do a scatter diagram of this data. I am then going to log the life expectancy data but not the GDP per capita data and do a scatter diagram of this data. Then finally I am going to log both my data for GDP per capita and the life expectancy at birth and do a scatter diagram. I am going to check which scatter diagram gives the strongest linear correlation and thats the data Im going to chose. Country Life expectancy at birth (years) Log of GDP per capita, Purchasing Power Parity ($) American Samoa 75.75 3.903089987 Anguilla 76.7 3.934498451 Armenia 66.68 3.556302501 Bahamas, The 65.71 4.184691431 Barbados 71.84 4.176091259 Benin 51.08 3.041392685 Bolivia 64.78 3.397940009 British Virgin Islands 76.06 4.204119983 Burma 55.79 3.230448921 Cameroon 48.05 3.230448921 Central African Republic 41.71 3.079181246 China 72.22 3.672097858 Congo, Democratic Republic of the 48.93 2.77815125 Cote dIvoire 42.65 3.146128036 Djibouti 43.13 3.113943352 East Timor 65.2 2.698970004 El Salvador 70.62 3.662757832 Ethiopia 41.24 2.84509804 French Guiana 76.69 4.158362492 Gambia, The 54.38 3.255272505 Ghana 56.53 3.301029996 Grenada 64.52 3.698970004 Guatemala 65.23 3.591064607 Guinea-Bissau 46.97 2.84509804 Honduras 66.65 3.397940009 India 63.62 3.414973348 Iraq 67.81 3.380211242 Jersey 78.93 4.394451681 Kenya 45.22 3.041392685 Korea, South 75.36 4.292256071 Laos 54.3 3.255272505 Liberia 48.15 3 Macau 81.87 4.267171728 Malaysia 71.67 3.944482672 Malta 78.43 4.235528447 Martinique 78.72 4.029383778 Mayotte 60.6 2.77815125 Monaco 79.27 4.431363764 Morocco 70.04 3.591064607 Nauru 61.95 3.698970004 New Caledonia 73.52 4.146128036 Nigeria 51.01 2.954242509 Pakistan 62.2 3.301029996 Papua New Guinea 64.19 3.322219295 Philippines 69.29 3.662757832 Reunion 73.43 3.748188027 Saint Helena 77.38 3.397940009 Saint Pierre and Miquelon 78.11 4.041392685 San Marino 81.43 4.539076099 Saudi Arabia 68.73 4.056904851 Country GDP per capita, Purchasing Power Parity ($) Log of Life expectancy at birth Log (years) American Samoa 8000 1.879382637 Anguilla 8600 1.884795364 Armenia 3600 1.823995591 Bahamas, The 15300 1.817631467 Barbados 15000 1.856366324 Benin 1100 1.708250889 Bolivia 2500 1.811440944 British Virgin Islands 16000 1.881156321 Burma 1700 1.746556361 Cameroon 1700 1.681693392 Central African Republic 1200 1.62024019 China 4700 1.858657484 Congo, Democratic Republic of the 600 1.689575216 Cote dIvoire 1400 1.629919036 Djibouti 1300 1.634779458 East Timor 500 1.814247596 El Salvador 4600 1.848927713 Ethiopia 700 1.615318657 French Guiana 14400 1.884738738 Gambia, The 1800 1.735439203 Ghana 2000 1.752278985 Grenada 5000 1.809694359 Guatemala 3900 1.814447379 Guinea-Bissau 700 1.67182056 Honduras 2500 1.823800154 India 2600 1.803593665 Iraq 2400 1.831293744 Jersey 24800 1.897242103 Kenya 1100 1.655330558 Korea, South 19600 1.87714089 Laos 1800 1.73479983 Liberia 1000 1.682596291 Macau 18500 1.91312479 Malaysia 8800 1.855337404 Malta 17200 1.894482215 Martinique 10700 1.896085085 Mayotte 600 1.782472624 Monaco 27000 1.899108858 Morocco 3900 1.845346137 Nauru 5000 1.792041311 New Caledonia 14000 1.866405498 Nigeria 900 1.707655324 Pakistan 2000 1.793790385 Papua New Guinea 2100 1.807467376 Philippines 4600 1.840670561 Reunion 5600 1.865873528 Saint Helena 2500 1.888628725 Saint Pierre and Miquelon 11000 1.892706638 San Marino 34600 1.910784435 Saudi Arabia 11400 1.837146344 Country Log of GDP per capita, Purchasing Power Parity Log ($) Log of Life expectancy at birth Log (years) American Samoa 3.903089987 1.879382637 Anguilla 3.934498451 1.884795364 Armenia 3.556302501 1.823995591 Bahamas, The 4.184691431 1.817631467 Barbados 4.176091259 1.856366324 Benin 3.041392685 1.708250889 Bolivia 3.397940009 1.811440944 British Virgin Islands 4.204119983 1.881156321 Burma 3.230448921 1.746556361 Cameroon 3.230448921 1.681693392 Central African Republic 3.079181246 1.62024019 China 3.672097858 1.858657484 Congo, Democratic Republic of the 2.77815125 1.689575216 Cote dIvoire 3.146128036 1.629919036 Djibouti 3.113943352 1.634779458 East Timor 2.698970004 1.814247596 El Salvador 3.662757832 1.848927713 Ethiopia 2.84509804 1.615318657 French Guiana 4.158362492 1.884738738 Gambia, The 3.255272505 1.735439203 Ghana 3.301029996 1.752278985 Grenada 3.698970004 1.809694359 Guatemala 3.591064607 1.814447379 Guinea-Bissau 2.84509804 1.67182056 Honduras 3.397940009 1.823800154 India 3.414973348 1.803593665 Iraq 3.380211242 1.831293744 Jersey 4.394451681 1.897242103 Kenya 3.041392685 1.655330558 Korea, South 4.292256071 1.87714089 Laos 3.255272505 1.73479983 Liberia 3 1.682596291 Macau 4.267171728 1.91312479 Malaysia 3.944482672 1.855337404 Malta 4.235528447 1.894482215 Martinique 4.029383778 1.896085085 Mayotte 2.77815125 1.782472624 Monaco 4.431363764 1.899108858 Morocco 3.591064607 1.845346137 Nauru 3.698970004 1.792041311 New Caledonia 4.146128036 1.866405498 Nigeria 2.954242509 1.707655324 Pakistan 3.301029996 1.793790385 Papua New Guinea 3.322219295 1.807467376 Philippines 3.662757832 1.840670561 Reunion 3.748188027 1.865873528 Saint Helena 3.397940009 1.888628725 Saint Pierre and Miquelon 4.041392685 1.892706638 San Marino 4.539076099 1.910784435 Saudi Arabia 4.056904851 1.837146344 You can see from the scatter diagrams that the log of GDP per capita against the life expectancy shows the strongest linear correlation so that is the one I am going to choose. Therefore this means that I am going to use the data for log of GDP per capita and the life expectancy at birth. From the scatter diagram I can see that there is a positive correlation between the two variables. From looking at the scatter diagram I can see that the data takes an elliptical shape. Since the ellipse appears to be quite narrow it implies that there is a good positive correlation i.e. as one variable increases, so does the other. Therefore the data shows a clear linear relationship. Another technique that I am going to use is a histogram because you are able to see the distribution clearly and able to determine whether I can use Pearsons product moment correlation (PMCC) or Spearmans coefficient of rank order. I am going to draw a histogram for each variable and if the distribution is not normally distributed I shall use Spearmans and if it is I shall use PMCC. As the histograms roughly show a normal distribution I am going to use PMCC method. Analysis: Now I am going to calculate the PMCC with the help of Microsoft Excel. x y x2 y2 XY 75.75 3.903089987 5738.063 15.23411 295.6591 76.7 3.934498451 5882.89 15.48028 301.776 66.68 3.556302501 4446.222 12.64729 237.1343 65.71 4.184691431 4317.804 17.51164 274.9761 71.84 4.176091259 5160.986 17.43974 300.0104 51.08 3.041392685 2609.166 9.250069 155.3543 64.78 3.397940009 4196.448 11.546 220.1186 76.06 4.204119983 5785.124 17.67462 319.7654 55.79 3.230448921 3112.524 10.4358 180.2267 48.05 3.230448921 2308.803 10.4358 155.2231 41.71 3.079181246 1739.724 9.481357 128.4326 72.22 3.672097858 5215.728 13.4843 265.1989 48.93 2.77815125 2394.145 7.718124 135.9349 42.65 3.146128036 1819.023 9.898122 134.1824 43.13 3.113943352 1860.197 9.696643 134.3044 65.2 2.698970004 4251.04 7.284439 175.9728 70.62 3.662757832 4987.184 13.41579 258.664 41.24 2.84509804 1700.738 8.094583 117.3318 76.69 4.158362492 5881.356 17.29198 318.9048 54.38 3.255272505 2957.184 10.5968 177.0217 56.53 3.301029996 3195.641 10.8968 186.6072 64.52 3.698970004 4162.83 13.68238 238.6575 65.23 3.591064607 4254.953 12.89575 234.2451 46.97 2.84509804 2206.181 8.094583 133.6343 66.65 3.397940009 4442.223 11.546 226.4727 63.62 3.414973348 4047.504 11.66204 217.2606 67.81 3.380211242 4598.196 11.42583 229.2121 78.93 4.394451681 6229.945 19.31121 346.8541 45.22 3.041392685 2044.848 9.250069 137.5318 75.36 4.292256071 5679.13 18.42346 323.4644 54.3 3.255272505 2948.49 10.5968 176.7613 48.15 3 2318.423 9 144.45 81.87 4.267171728 6702.697 18.20875 349.3533 71.67 3.944482672 5136.589 15.55894 282.7011 78.43 4.235528447 6151.265 17.9397 332.1925 78.72 4.029383778 6196.838 16.23593 317.1931 60.6 2.77815125 3672.36 7.718124 168.356 79.27 4.431363764 6283.733 19.63698 351.2742 70.04 3.591064607 4905.602 12.89575 251.5182 61.95 3.698970004 3837.803 13.68238 229.1512 73.52 4.146128036 5405.19 17.19038 304.8233 51.01 2.954242509 2602.02 8.727549 150.6959 62.2 3.301029996 3868.84 10.8968 205.3241 64.19 3.322219295 4120.356 11.03714 213.2533 69.29 3.662757832 4801.104 13.41579 253.7925 73.43 3.748188027 5391.965 14.04891 275.2294 77.38 3.397940009 5987.664 11.546 262.9326 78.11 4.041392685 6101.172 16.33285 315.6732 81.43 4.539076099 6630.845 20.60321 369.617 68.73 4.056904851 4723.813 16.45848 278.8311 Totals 3224.34 179.0276425 215012.6 653.5361 11793.26 This shows that my variables have a good positive correlation. I am now going to carry out a hypothesis test on the correlation coefficient to see if there is enough evidence from my sample to conclude that there is correlation in the whole population. : ? = 0 (There is no correlation between the two variables in all the countries in the world) : ? 0 (Positive Correlation) N= 50 I will be doing a one tail test at the 5% significant level So the critical value = 0.2353 So 0.833872644 0.2353 Therefore I can conclude that there is enough evidence from the sample to say that I accept that there is a positive correlation. Regression line The equation of the regression line is: As you can see on the page here is my scatter diagram with the regression line drawn on it which was all done in excel. This is Y upon X regression line. Interpretation: From the investigation that I have carried out I have discovered that that there is a positive correlation between my two sets of data which is shown on my graph and regression line. The aim of my investigation was to see if there is any correlation between the GDP per capita ($) of a country and the life expectancy at birth (years). I can now confidently say that I have achieved my aim as there is a positive correlation as predicted. The sample that I took is of the whole world and is a good representation of the whole population. By using the correlation results I can predict if there was a country with a low GDP then it is expected that they have a low average life expectancy. This trend would be expected for every country in a similar position but some countries may incur lower life expectancies than normal due to some external factor e.g. war, outbreak of a new disease or some sort of natural disaster. But regardless of these exceptions they shall not affect the overall correlation. I think that this data was worth investigating and collecting because I now realise how important the GDP per capita of a country is in affecting how long a person lives and how the higher the GDP the better the quality of life is for a person. This investigation has shown that people living in developing countries are more likely to die at a young age and will not have such a high quality of life as we enjoy in a country like the UK. I also think this investigation will act as very good evidence to try and convince richer nations to help poorer ones. This data should be given to an organisation like the United Nations to try an act as a catalyst to convince them to do something about this before it is too late. Accuracy and refinements: One possible source of error was that the data may have been displayed incorrectly on the website or I may have copied it incorrectly. I would improve this by comparing data from a number of different sources to ensure accurate and reliable results. The sampling method that I used could have been a possible source of error. This is because my systematic sample only included every 4th so for example every 3rd did not have a chance to be chosen. I could have improved my sampling method by using simple random sampling instead of systematic sampling. Simple random sampling ensures that every item of data has an equal chance of being chosen. This is a very important factor in ensuring the reliability of my work. Even though the data is very reliable there are some improvements that could be made. First of all the data was only collected for a given year in my case it was for 2003. For more accurate data I could have used data over five years to see if there is actually a difference and to see if for example at that given years there may have been a low life expectancy due to an external factor like war or disease. Also the sample was only from 228 countries and there are more countries in the world so a more fair representation would be to random sample from every country in the world. This was not possible because my source did not include some of these countries due to political reasons and from lack of information for those countries. In my investigation I had to reject 11 statistics for 11 countries this reduced the randomness of my sample. I would improve this by making sure that data was available for every item in the parent population. Overall I am very happy with the accuracy and reliability of my data because I got it from a very reliable source which was www.CIA.gov. Having a reliable source for my data enables me to achieve my aim of a positive correlation.

Overcoming Mount Redcloud My Creative Writing teacher wanted us to write a paper over something we had experienced, but she wanted it in the form of fiction.

Overcoming Mount Redcloud My Creative Writing teacher wanted us to write a paper over something we had experienced, but she wanted it in the form of fiction. Overcoming Mount Redcloud"Rise and shine!" shouted Joanna as she pulled the curtains back. "What the hell time is it?" Jordan's thought process wasn't so great at this hour. She rolled over and pulled a pillow over her head. "5:30!" exclaimed Joanna, and yanked the pillow out of Jordan's arms. "You mean they have one of those in the morning too?" Jordan moaned. Joanna giggled. "Come on sleepyhead! You can take a shower first so you can wake yourself up. You'll need it." She looked around the room for a few seconds. "Here. You'll need these too." She said as she tossed Jordan's hiking boots over to her side of the hotel room. Joy, Jordan thought. Another fun-filled day of hiking up that hideous trail with the icky tarantulas and huge scorpions as well as other crawly creatures. She was a city girl, and her and The Great Outdoors didn't get along very well.JoannaThey just couldn't see eye to eye. Jordan was a girly girl, and wasn't a fan of hiking adventures and creatures and getting d irty. Joanna, on the other hand, was very competitive, and very athletic. She was the cutest little half Korean girl, with adorable chubby cheeks, but nothing could stand in her way. She loved doing outdoorsy-type stuff with her dad. The only thing they had in common was that they were both 15, and they both played the trombone in the high school band together. But they had been best friends since Joanna had moved to Jordan's high school at the beginning of the past school year. And this year, on her family's summer vacation to Colorado, she had invited Jordan to come along with her and her dad and her sweet little Korean mom. Oh yeah. The authentic Korean food. That was a big enough adventure for Jordan in itself. Much different than any other Asian food she had ever experienced. But apparently it wasn't enough for Joanna. "Me and you and dad are gonna hike a 14er." Joanna said. "Huh?" "Mt. Recloud. We're gonna hike it. It's over 14,000 feet high. 14,037, to be exact." Jordan stare d at Joanna. She couldn't be serious. Didn't she know how inexperienced Jordan was at this whole hiking thing? She'd had enough trouble hiking up that mini-mountain behind the hotel. And it was a high one. "Really...?" was all Jordan could squeak out. "Yeah! It's gonna be so great! I can't wait to get up to the summit and breathe the fresh mountain air!! Now go shower so we can go!!" Assuming there was no argument, Jordan grabbed some clothes and headed toward the shower. She was enjoying the trip, and was very grateful that Joanna and her family had invited her. But she just wasn't enjoying the outdoor-type thing. She kind of wished Joanna had taken into consideration that she was barely even a beginner as far as the whole hiking thing went. But she didn't wanna say anything, because she didn't want to offend her best friend, especially after she had invited her to go on this trip.After the girls got ready, they went next door to Joanna's parents room and knocked on the door. They were greeted by Joanna's mother's smiling face and "Good morning girls" in her broken English. Her dad was sitting on the bed eating a donut and watching the weather. "It's gonna be a good day for hiking! The high is only 70 and its supposed to be sunny all day. Are y'all ready?" Joanna nodded eagerly, and Jordan just looked at her. "Alright, let's hit the road!!" "Bye-bye! Have fun and be careful!" Joanna's mother said. "We will!" Joanna said over her shoulder as they walked out the door.About 30 minutes later, they were at the foot of Jordan's enemy. Mount Redcloud, in all its glory, towered high above their heads. Jordan was more intimidated than she had ever been in her whole life. In a few hours, the three of them would be standing exactly 14,037 feet higher than they were at the moment, on the summit. "Okay, if we want to reach the summit by noon, we had better start now." Joanna's dad said. So the three of them picked up their backpacks, threw them over their shoulders and ba sically just dug in. For Jordan, this was terribly overwhelming. But she began to realize that in the end, she would probably be glad that she did this. She picked up a tall, thick stick and used it to help pull her up as she hiked the trail that led to the summit. Joanna's dad was just a few feet ahead of her, occasionally checking to see if Jordan was okay, and stopping to wait on her. "Geez, Joanna is a mountain goat!" Jordan exclaimed as she watched Joanna effortlessly float up the mountain, not once looking back. "Yeah, she loves this type of thing. She loves coming to Colorado and hiking and mountain biking and rock climbing and propelling and all sorts of stuff. For her this is taking it easy. She figured it would be fairly easy for you but still be something fun for her." "How sweet." Jordan said, partly under her breath.After what seemed like forever, the trio reached the halfway point. So they decided to take a rest and have a piece of fruit and some water. They took a sea t under some shade and relaxed for awhile. "How are you holding up, kiddo?" Joanna asked Jordan as she swigged a huge gulp of water. "Pretty good, i guess. Better than i thought i would for sure. You make me sick, you know that?" She splashed some water on Joanna. "Heeyy!! I'm sorry im so GOOD at this!!" Joanna squealed, and splashed some water back at Jordan. "You're doing alot better, sport." Joanna's dad said to her. "Seems like you've gotten alot faster since last year." "Yeah, i guess staying in cross country and cheerleading has something to do with it. I tried to stay in shape this year." After about half an hour, they decided to finish the ascend toward the summit. Almost there, Jordan thought.The rest of the hike was grueling, to say the least. Jordan got more and more exhausted, Joanna's dad had to stop alot more often, and even Joanna had begun to slow down a great deal. The air had gotten thinner the higher they got, and it had gotten cooler as well. Not to mention they had been hiking up this very steep mountain since about 6:45 that morning, with only a 30 minute break. And the higher they got, the more tired they all became. Eventually they were all very close together, going at a much slower pace than they had started off at. Finally, Joanna's dad perked up. "Look, we have 10 feet to the summit!" Lovely! They sped up slightly, hoping to reach the top very soon. After about 10 minutes, they made it. The view was breathtaking. Jordan could hardly believe her eyes. She had never seen anything like it. Her jaw dropped and the whole thing was just exhilarating. "Are you glad you came Jordan?" Joanna asked. "Yes. WOW." was all Jordan could mutter. She was just so impressed with what she saw. She couldn't believe that she didn't want to do this. She couldn't believe that God had made what she saw in only a few days, and she was too stubborn to want to enjoy it earlier this morning. "That's Sunshine Peak, and the connecting ridge. Over there is Handies Peak. And that's Cinnamon Pass Road beside it." Joanna's dad was pointing stuff out. The three of them stayed at the summit for about 20 more minutes, looking around and admiring the view. Jordan just took everything in. She was so glad that she took the opportunity to do this. Now she could say that she too, had hiked a 14er. "Alright guys, time to head back. We need to go to the hotel and get some rest so we can get up early and go white water rafting tomorrow." Jordan and Joanna looked at each other. Joanna grinned from ear to ear. "Race you to the bottom!!"

What Does It Take to Get Into the University of Colorado--Boulder?

Breathtaking vistas. Exceptional academics. Outdoor adventure. These are just a few of the reasons that students choose the University of Colorado–Boulder to pursue their educations. Widely regarded as one of the most beautiful colleges in the U.S., this institution offers dozens of academic programs in a range of fields, along with ample varsity sports and extracurriculars. It’s also one of the world’s most exciting centers for research and innovation. Wondering if the University of Colorado–Boulder is the school for you? Find out what it takes to get into this institution, along with important dates and deadlines for your application. If your college journey is taking you to the Centennial State, it pays to do your research regarding important dates and deadlines. Students hoping to matriculate at the University of Colorado–Boulder need to apply by November 15th for Early Action and January 15th for Regular Decision . They also need to submit the following application materials: Note that you can request an application fee waiver on the Common Application. The University of Colorado–Boulder has a relatively high acceptance rate. Of the 36,000 students who applied to CU Boulder last year, the university accepted around 29,000, for an acceptance rate of approximately 80%. So, if your heart is set on attending this university, the good news is you have a high likelihood of getting in. If you’re planning to apply to this Western institution, you will be required to select a major program. Some colleges and programs at CU Boulder are more competitive than others, so read up on the academic requirements for your particular major prior to applying. Consider whether your current GPA and test scores are in the admissions range or if you need to take some steps to improve your academic standing before applying. Note that applicants not selected for admission in the business, environmental design, media, communication and information, music, or engineering programs are automatically considered for admission to the College of Arts and Sciences. So even if you aren’t selected for your first choice program, you can still be accepted to the university. Estimating your chance of getting into a college is not easy in today’s competitive environment. Thankfully, with our state-of-the-art software and data, we can analyze your academic and extracurricular profile and estimate your chances. Our profile analysis tool can also help you identify the improvement you need to make to enter your dream school. CU Boulder prides itself on practicing a holistic admission review process when evaluating potential students. Along with considering academic factors like GPA and test scores, the University of Colorado–Boulder strives to assess each applicant as an individual by looking at extracurriculars, after-school jobs, leadership activities, as well as any extenuating circumstances. In particular, the University of Colorado–Boulder evaluates essays and letters of recommendation to determine the ways in which a student contributed to their school and community. The goal is to determine which students would be successful in the school’s competitive learning environment. With regard to academic achievement, CU Boulder seeks out students who excelled at the high school level. For 2018, the middle 50% of accepted freshmen boasted GPAs between 3.49 and 4.0 with percentile ranks between 68% and 93%. The school also favors applicants who challenged themselves by taking advanced, honors, AP, and IB courses, while satisfying its Minimum Academic Preparation Standards (MAPS). The required coursework includes: CU Boulder also puts a strong emphasis on test scores. For 2018, the average SAT scores for admitted freshmen ranged from 1180 to 1370. Students who took the ACT earned between a 26 and a 31.   Because student essays play such a crucial role in CU Boulder admissions decisions, it pays to invest extra time and effort into this component of your application. The university expresses a preference for students who don’t submit cookie cutter essays. Instead, students should write about topics that are meaningful to them and use personal anecdotes to get their points across. Along with showcasing excellent written communication skills, essays should be honest and engaging. The goal is to convey the journey that has brought you to this point, even if there were some bumps along the way. Additionally, aspiring CU Boulder students can get a leg up on the competition by focusing on their leadership efforts. Did you hold a position on student council? Chair a committee for your high school’s National Honor Society? Coach a youth sports team? The most competitive students shine in both their schools and their towns. Finally, University of Colorado–Boulder students may be able to gain an academic edge by taking the SAT more than once. Because CU Boulder is one of a number of schools that superscores the SAT—meaning it takes the highest score for each section regardless of testing attempt—students may be able to improve their profiles by taking the test again. No one likes to feel like they failed at something they set out to achieve. Unfortunately, rejection is a natural part of the admissions process, and very few people accomplish all their goals the first time around. Though you may feel like sulking for a few days after receiving a rejection letter, it’s important to jump back into your college search as soon as possible. If you’re concerned about getting accepted to CU Boulder, it pays to have a backup plan. You might want to consider applying to some schools considered similar to University of Colorado–Boulder, including Colorado State University–Fort Collins and the University of Arizona. At , we’re passionate about helping students get the personalized support they need to attend their dream colleges. From helping students narrow down their college application lists to finding opportunities to maximize financial aid, we strive to make the process of applying to colleges more efficient while keeping stress levels low. To learn more about how we can help you achieve your goals, call today or join our Applications Program online .

Discuss the ethical issues in the Monsanto case Essay - 1

Discuss the ethical issues in the Monsanto case - Essay Example The company in the recent times has been involved in dictating on what the world consumes. The company has continued to generate many biotech crops. The company however has generated controversies in the world due to the issue of production of biotech crops that are produced and increasing the control of food supply by huge corporations. The company before getting involved in seed technology was involved in production of chemicals. Production of crops and new seeds through biotechnology by the company has predicted doubling of food production in the future meeting the food demand of the growing population. Food security will be maintained by the company. The company has also formed coalitions with other public researchers and charitable organization to focus on green revolution to allow conservation of the environment with production of more food and inventions to satisfy food need of the population. The organization has made itself to be in the leading dealing with advancement in global fight against hunger. Working with other organization in poor nations, the company helps to reach needy farmers. Moves that are made by the company is seen to be parallel to the commercial sales that are made by the organization. The organization upholds its principles by encouraging farmers that are in the poor nations and do not concentrate much in improving those in the wealthy nations. In the sales of the organization, sales of seeds and chemicals that are of high prices are done to countries that are wealthy (Forrestal, 2007). These products are sold to farmers in poor countries in low prices. The organization has been encouraged by the department of agriculture in the United States and the government to incorporate public institutions, foundations and academics to determine how the production can be improved to make food abundant globally. The company before getting involved in seed technology was involved in production

Write a story of your own Assignment Example | Topics and Well Written Essays - 250 words

Write a story of your own - Assignment Example The family noticed a very heavy traffic jam on the highway. Another peculiar thing that could be observed was the sudden change in weather with very strong winds. It was then that they turned on the radio and they were updated by their relatives that a hurricane had struck the city. The cars on the road seemed like ants stranded here and there. This was not all but matters became worse when the radio announcement claimed that the hurricane was moving towards the highway. A chaotic situation was created with common sites of cars banging into each other. But Harry and his family were lucky again because a following announcement pronounced that the hurricane had taken the other route and the situation had resolved. This organized day presented with an unpredictable happening. The family experienced a very difficult time and though they reached home in 2 days, but the following two weeks were very difficult with no electricity and basic resources. Despite the advances in human technology, there are still certain areas which are out of human control and the sudden weather changes are one of

Growing Up as an All-American Kid :: Personal Narrative Football Sports Essays

Growing Up as an All-American Kid Growing up is not an easy thing to do. You have no idea what is going on with your body, your emotions change at the drop of a hat, and you sometimes wonder what the point of life is. However, what you do know is that Mercer is planning a party after the game Friday night and you need to be there. This is the way I seem to remember high school when I think about it for a brief second. However, when I sit down and actually give it some thought, I realize that there is so much more about those years I have forgotten about--all of the little things that happened to everyone everyday and those major events that seemed to change my life. Everything that went into making us All-American kids. Growing up in a small mid-western town was exactly like a lot of people imagine it to be. The years kept passing by, but it seemed like nothing ever changed. We went to school, played sports, chased girls, worked on our friend’s father’s farms, and talked about how we couldn’t wait until we graduated so that we could finally move out. Even though we were growing up in a typical town and living typical high school lives, it seemed like so much more. No one cared about anything except what they were going to do that night and there wasn’t a thing anyone could do about it. We were young and alive. I think my football coach referred to it as, â€Å"Being full of piss and vinegar.† Maybe we were, and we might have bitched and moaned, but deep down inside I think we loved every minute of it. From proms and parties, secret crushes and that first kiss, to shooting pool and playing video games, there was always something going on. For me it was as simple as sitting on my best friend’s roof smoking a cigar in the middle of winter, or as difficult as hugging one of my best female friend’s on my front porch while she cried because she was seventeen years old and had just had an abortion. No one knew what was going to happen next, and I think that was part of what made life seem so invigo rating.

What is the Future of Internet Radio?

Since the days when the family radio was a focal point of the home, where everyone gathered as the main source of news and entertainment to the present day of Internet, satellite and digital radio content, the basic concept of radio has not only survived, but thrived. With all of the new options in radio, however, the question of the future of Internet radio has generated many ideas, controversy and discussion over the past several years. This essay will take a balanced approach to discussing both the pros and cons of Internet versus traditional radio in an effort to ultimately answer this question in an intelligent way. Will Internet Radio Replace Traditional Radio? The knee-jerk tendency when considering whether or not Internet radio will replace traditional radio would be to assume that this would be the case if for no other reason than due to the natural progression of technology, much like the compact disc eventually replaced the vinyl record and the like. However, a closer look at the question requires that a more thorough review of source material take place before jumping to conclusions. In less than a decade, Internet radio has gained the same status as a mass media source as radio has over approximately the last century-clearly a force with which to be reckoned (VanHorn). This begs the question of how this was able to take place so rapidly and whether it is due to the faddish nature of some new technologies or because of distinct advantages that Internet has over conventional radio. Few would argue that the massive increase in the availability of Internet access over the past several years has added to the power of the medium- this includes not only the fact that most every workplace in America has some level of Internet access for most employees, but also that Internet access has been made available to the vast majority of households across a range of economic classes, races and cultures. With this, a new group of media consumers has evolved. Called â€Å"streamies†, these individuals are those who use the Internet for shopping, communication, work, and media/entertainment access (VanHorn). The streamies are now beginning their second, and in some cases third generation, with children gaining access to the Internet as soon as they are able to point and click a computer mouse. So, we see a well established and growing audience for Internet radio. Internet radio producers have not been blind to the fact that they are looking at a seemingly endless supply of listeners and that the future potential is all but endless. Knowing that this audience is technologically savvy, and harnessing the power of the Internet, there have been many enhancements to the Internet radio experience that in fairness are hard for conventional radio to compete with, including interactive broadcasts that allow listeners to provide feedback to broadcasters, blogs that allow for the audience to communicate with each other, and additional Websites which could give a listener access to other materials of interest. Evidence suggests that this type of multimedia experience is very well suited to the modern person, who not only wishes to hear a media source, but also wishes to have something to watch or that will give the chance for one’s intellect to be exercised (Crisell). While Internet radio seems to have quite an assortment of options to offer to the modern audience member, traditional radio should not be counted out just yet. From the advent of Internet radio, traditional radio has attempted to slow down the proliferation of competing Internet radio, first through lawsuits which alleged that Internet broadcasters were taking unfair advantage of the broadcasting system because of the fact that they were exempt from many of the regulations which at times saddle the traditional radio broadcaster and represent a huge expense for them (Mckibben). Failing that, the traditionalists have in recent years likewise gotten involved in Internet broadcasting, using online technology to reach a wider audience with the content that was popular with conventional listeners for years in the past (Crisell). It would appear that in the present stalemate between Internet and conventional radio, the future for both seems cloudy. However, as we will see in a later portion of this essay, there is a very viable future that remains to be seen. Should Internet Radio Pay the Same Royalties as Traditional Radio? The point was made earlier that conventional radio has long argued that Internet radio has unfair advantage in areas such as regulation, technological requirements, etc. Another consideration that has financial implications is the question of whether or not Internet radio should pay the same royalties as traditional radio if the two media sources are different but fundamentally similar. Ironically, when discussing royalties, Internet broadcasters have a disadvantage over conventional broadcasters, at least on the surface. Conventional broadcasters pay a set royalty into order to broadcast copyrighted materials such as songs, whereas Web-based broadcasters are charged a fee per download. Therefore, given the huge size of online audiences that do not have the limitations like those who receive broadcasts on regular radios, royalty fees can quite literally be without limit (Harwood). On the other hand, the possibility of endlessly large audiences, if properly marketed, can result in substantially larger advertising revenue if advertisers can be convinced of the value of such large target audiences for their message. With the evidence that exists, it would seem that the answer would be not to arbitrarily assess higher royalty fees to Internet broadcasters, or to lower fees to traditional broadcasters to try to give them some sort of competitive edge over the massive power of online broadcasters, but to find a way to create a percentage-based royalty fee for both media sources. For example, Internet broadcasters who are mostly content-based and do not emphasize a large amount of advertising would not be held responsible for massive royalty payments since the content they are utilizing is not being used for the purposes of driving massive revenues in the first place. Conversely, when Internet content results in massive advertising revenue, it would only make sense that royalties be fairly paid for the content that made the profits possible. Careful auditing and a process of verification for the numbers that are used to determine the royalty rates would alleviate any possible errors and disputes from the outset. What Does the Future Hold? The point was earlier made that the destruction of traditional radio in favor of Internet radio may not be what the future holds, and there are compelling reasons for making that assumption, for as cutting-edge and attractive as Internet radio may be, there is something to be said for the grass roots way that traditional radio operates, serves and entertains. In times of emergency and local interest, people will always look to the traditional, local radio station for what they crave-something that computer servers and satellites from around the globe simply cannot provide, as if they are too big and cumbersome to be as nimble and versatile as the smaller broadcasters in the traditional sense tend to be (Armstrong). Also, as was said earlier, traditional broadcasters can likewise participate in Internet broadcasting while still retaining their local ties and flavor. Therefore, it is quite reasonable to predict that the future will save a place for the traditional, and cutting edge broadcasting worlds. Conclusion At the risk of sounding outrageous, there are surely new applications of broadcasting technology that currently exist only in the minds of those trying to make them a reality. Therefore, in closing, the point should also be made that radio, to paraphrase a line from a classic song, has only just begun.