Science Terms and Definitions You Should Know

Science Terms and Definitions You Should Know Scientific experiments involve variables, controls, a hypothesis, and a host of other concepts and terms that may be confusing. This is a glossary of important science experiment terms and definitions. Glossary of Science Terms Central Limit Theorem: states that with a large enough sample, the sample mean will be normally distributed. A normally distributed sample mean is necessary to apply the t test, so if you are planning to perform a statistical analysis of experimental data, its important to have a sufficiently large sample. Conclusion: determination of whether the hypothesis should be accepted or rejected. Control Group: test subjects randomly assigned to not receive the experimental treatment. Control Variable: any variable that does not change during an experiment. Also known as constant variable Data:  (singular: datum) facts, numbers, or values obtained in an experiment. Dependent Variable: the variable that responds to the independent variable. The dependent variable is the one being measured in the experiment. Also known as the dependent measure, responding variable double-blind: neither the researcher nor the subject knows whether the subject is receiving the treatment or a placebo. Blinding helps reduce biased results. Empty Control Group: a type of control group which does not receive any treatment, including a placebo. Experimental Group: test subjects randomly assigned to receive the experimental treatment. Extraneous Variable: extra variables (not the independent, dependent, or control variable) that may influence an experiment, but are not accounted for or measured or are beyond control. Examples may include factors you consider unimportant at the time of  an experiment, such as the manufacturer of the glassware in a reaction or the color of paper used to make a paper airplane. Hypothesis: a prediction of whether the independent variable will have an effect on the dependent variable or a prediction of the nature of the effect.   Independence  or  Independently:  means one factor does not exert influence on another. For example, what one study participant does should not influence what another participant does. They make decisions independently. Independence is critical for a meaningful statistical analysis. Independent Random Assignment: randomly selecting whether a test subject will be in a treatment or control group. Independent Variable: the variable that is manipulated or changed by the researcher. Independent Variable Levels: refers to changing the independent variable from one value to another (e.g., different drug doses, different amounts of time). The different values are called levels. Inferential Statistics: applying statistics (math) to infer characteristics of a population based on a representative sample from the population. Internal Validity: an experiment is said to have internal validity if it can accurately determine whether the independent variable produces an effect. Mean: the average calculated by adding up all the scores and then dividing by the number of scores.   Null Hypothesis: the no difference or no effect hypothesis, which predicts the treatment will not have an effect on the subject. The null hypothesis is useful because it is easier to assess with a statistical analysis than other forms of a hypothesis. Null Results (Nonsignificant Results): results that do not disprove the null hypothesis. Null results dont prove the null hypothesis, because the results may have resulted from a lack of power. Some null results are type 2 errors. p 0.05: This is an indication of how often chance alone could account for the effect of the experimental treatment. A value p 0.05 means that 5 times out of a hundred, you could expect this difference between the two groups, purely by chance. Since the chance of the effect occurring by chance is so small, the researcher may conclude the experimental treatment did indeed have an effect. Note other p or probability values are possible. The 0.05 or 5% limit simply is a common benchmark of statistical significance. Placebo (Placebo Treatment):  a  fake treatment that should have no effect, outside of the power of suggestion. Example: In drug trials, test patients may be given a pill containing the drug or a placebo, which resembles the drug (pill, injection, liquid) but doesnt contain the active ingredient. Population: the entire group the researcher is studying. If the researcher cannot gather data from the population, studying large random samples taken from the population may be used to estimate how the population would respond. Power: the ability to observe differences or avoid making Type 2 errors. Random or Randomness: selected or performed without following any pattern or method. To avoid unintentional bias, researchers often use random number generators or flip coins  to make selections. (learn more) Results: the explanation or interpretation of experimental data. Statistical Significance: observation, based on the application of a statistical test, that a relationship probably is not due to pure chance. The probability is stated (e.g., p 0.05) and the results are said to be statistically significant. Simple Experiment: basic experiment designed to assess whether there are a cause and effect relationship or test a prediction. A fundamental simple experiment may have only one test subject, compared with a controlled experiment, which has at least two groups. Single-blind: when either the experimenter or subject is unaware whether the subject is getting the treatment or a placebo. Blinding the researcher helps prevent bias when the results are analyzed. Blinding the subject prevents the participant from having a biased reaction. T-test: common statistical data analysis applied to experimental data to test a hypothesis. The t-test computes the ratio between the difference between the group means and the standard error of the difference (a measure of the likelihood the group means could differ purely by chance). A rule of thumb is that the results are statistically significant if you observe a difference between the values that are three times larger than the standard error of the difference, but its best to look up the ratio required for significance on a t table. Type I Error (Type 1 error): occurs when you reject the null hypothesis, but it was actually true. If you perform the t-test and set p 0.05, there is less than a 5% chance you could make a Type I error by rejecting the hypothesis based on random fluctuations in the data. Type II Error (Type 2 error): occurs when you accept the null hypothesis, but it was actually false. The experimental conditions had an effect, but the researcher failed to find it statistically significant.

Read This Before Applying to an Economics PhD Program

Read This Before Applying to an Economics PhD Program I recently wrote an article about the types of people who shouldnt pursue a Ph.D. in economics. Dont get me wrong, I love economics. Ive spent a majority of my adult life in the pursuit of knowledge in the field studying around the world and even teaching it at the university level. You may love studying economics, too, but a Ph.D. program is an entirely different beast that requires a very specific type of person and student. After my article was published, I received an email from a reader, who just happened to be a potential Ph.D. student.   This readers experience and insights into the economics Ph.D. program application process were so on point that I felt the need to share the insights. For those considering applying to a Ph.D. program in Economics, give this email a read. One Students Experience Applying to an Economics Ph.D. Program Thanks for the graduate school focus in your recent articles.  Three of the challenges you mentioned [in your recent article] really hit home: American students have a comparative disadvantage for selection compared to foreign students.The importance of math cannot be overstated.Reputation is a huge factor, especially that of your undergraduate program. I applied unsuccessfully to Ph.D. programs for two years before conceding that I might not be ready for them. Only one, Vanderbilt, gave me even a wait-list consideration. I was a little embarrassed at being shunned. My mathematics GRE was 780. I had graduated at the top of my class with a 4.0 GPA in my economics major and completed a statistics minor. I had two internships: one in research, one in public policy. And accomplished this all while working 30 hours a week to support me. It was a brutally hard couple of years. The Ph.D. departments I applied to and my undergraduate adviser all pointed out: I attended a small, regional public university, and our professors spent significant time with students to the detriment of their own publishing.Though I took a heavy load of statistics coursework, I only had two terms of calculus.I had never been published; not even in an undergraduate journal.I aimed for highly-ranked schools in the Midwest like Illinois, Indiana, Vanderbilt, Michigan, Wisconsin, Washington University in St. Louis, but neglected schools on the coasts, which might have seen me as a more diverse candidate. I also made what many considered a tactical error: I went to talk with the graduate programs before I applied. I was later told that this is a taboo and seen as schmoozing. I even talked at length with the director of one program. We ended up talking shop for two hours and he invited me to attend presentations and brown bags whenever I was in town. But soon I would learn that he would be ending his tenure to take a position at another college, and would no longer be involved in the approval process for that program. After going through these obstacles, some suggested I prove myself with a Masters Degree in Economics first. I had originally been told that many schools pick top candidates immediately after undergraduate, but this new advice made sense because departments commit considerable resources to their Ph.D. candidates and want to make sure their investment will survive first-year exams. With that path in mind, I found it interesting that so few departments offer a terminal Masters in Economic. Id say about half as many as those that offer only the terminal Ph.D. Fewer still offer an academic Masters - most of these are professional programs. Still, Im glad it gives me a chance to dig deeper into research and see if Im ready for Ph.D. research. My Response   This was such a great letter for many reasons. First, it was genuine. It wasnt a why didnt I get into a Ph.D. program rant, but a personal story told with thoughtful insights. In fact, my experience has been nearly identical, and I would encourage any undergraduate student considering pursuing a Ph.D. in economics to take this readers insights to heart. I, myself,  was in a Masters program (at Queens University in Kingston, Ontario, Canada) before I entered my Ph.D. program. Today, I must admit that I wouldnt have survived three months as a Ph.D. student had I not attempted an MA in Economics first.

The sun also rises Essay Example | Topics and Well Written Essays - 1000 words

The sun also rises - Essay Example Even though the generation following the war was usually referred to as â€Å"The Lost Generation†, the title of the book and its closing content is quite optimistic. Of course there may be many reasons why Hemingway chose this title and this paper will review his reasons for why he chose it. Jake Barnes, the main character and the narrator of the novel, was a veteran of The World War I, who later worked as a journalist in Paris. This book is a narration of the problems he had faced following the war and how he finally recovered from them. The author probably takes this as the theme behind the title. The initial pages of the book, recounts an injury that had caused many troubles to Jake, one among which included his inability to have sex. This had made Jack feel insecure about his masculinity and that he is less of a man that he was before. The fact that Brett, who was the love of his life, refused to enter into a relationship with Jake because of his impotency had made him feel very unhappy and depressed and had added to his insecurity. In many ways Jake was a typical member of what Gertrude Stein called â€Å"The Lost Generation†, which referred to the generation that experienced the grueling effects of World War 1, and when people had lost their belief in moral ity, faith and justice. The people of the Lost Generation lived an aimless life and spent their time engaged in worthless activities like boozing and dancing. In the early chapters of the book Jake’s character reminds the reader of the people of the Lost Generation, as he spent most of his time in the bar getting drunk. However, in the later chapters of the book and true its title, the sun does begin to shine on Jake. It narrates how Jake learned to find a solution for his problems, and how he no longer considered his impotency as a major issue. One realizes this for the first time when Jake goes out fishing in Burguete with his friend Bill Gorton. There, Jake truly enjoys his

Empirical paper on international finance or open economy Essay

Empirical paper on international finance or open economy macroeconomics - Essay Example A deep and well-supervised financial sector is essential for efficiently intermediating foreign finance into productive investments. It has also been shown to reduce the adverse effects of capital flow volatility. Countries with better institutions attract relatively more foreign direct investments and portfolio equity flows, which are more stable than debt flows, and as a result, the likelihood of promoting indirect benefits. For each of the threshold category, an appropriate and conceptually sound measure was chosen. Financial depth; the proxy used for financial depth is the ratio of private credit to GDP. Also include in the measure of financial depth and development are stock market capitalization sum and credit to the national GDP, the ratio of GDP and institution measures such as creditors’ rights ii. Institution quality; the proxy used to get aggregate institutional quality get derived from a simple average of the six World Bank Governance Indicators (WBGI). The six aspects of institutional quality covered by WBGI are: violence and profit stability; accountability and voice; quality of the regulatory; government effectiveness; the rule of law and control of corruption. iii. Regulation; the proxy used is an index of the rigidity of labor regulations from the International Finance Corporation’s Doing Business Database. The database captures an economy’s ability to adapt to changing business conditions that include financial flows. Since data is only available from 2003, average for each country is used as a fixed regulation variable. iv. Trade openness; the totals of imports and exports of goods and services, expressed as a ratio to GDP is used as the proxy. The measure of policy openness to trade can be defined as the proportion or level of years for which the trade regime/ era is an open one also got included. v. Macro policies; the

Personal Goals :: essays research papers

As a student at the University of Phoenix three personal goals that I want to achieve are, first is to complete my bachelor of science in business management in 2 years. Next is to become a better writer. Throughout junior college, writing has always been my weakest point and with the amount of writing assignments required at University of Phoenix this needs to be one of my top goals. Finally is to complete every course with no less than a B letter grade. With making the decision to return to school and taking on the considerable financial burden, receiving an average grade would be unacceptable to my standards.   Ã‚  Ã‚  Ã‚  Ã‚  While being employed full-time, The University of Phoenix has the rare opportunity for working professionals to finish courses in just 5 weeks. Having such a compressed time schedule for completing degrees will make it possible to complete my bachelor of science in business management in 2 years as long as I do not deviate from the program. I have decided that my number one priority in life is to complete my degree. I do not have other major commitments outside of work that will distract me from my assignments so staying focused on school will be realistic. Though I cannot predict the future, I do not plan on taking any time off during the two years that would result in interrupting my class schedule. With the option of taking CLEP test this will allow me to â€Å"test out† of some of the lower-division courses such as communication arts and humanities. Although this will require additional studying outside of my upper-division courses the CLEP test can hel p eliminate additional courses needed to be taken, so I can stay on track of my 2 year goal.   Ã‚  Ã‚  Ã‚  Ã‚  Writing papers has never been my strongest asset throughout school. I always found myself only writing what was required of me but never trying to improve my writing skills on my own time. In junior college the majority of my classes were math and science with a major in Administration of Justice. The only writing that I had to do was case briefs, which was based on legal research, which did not require any creativity, brainstorming and writing skills, just citing the facts and decisions in a proper format. To become a better writer it will take self-discipline and dedication. Because writing is my weakest point, submitting quality papers will require the most amount of my time by doing research and proofreading. Personal Goals :: essays research papers As a student at the University of Phoenix three personal goals that I want to achieve are, first is to complete my bachelor of science in business management in 2 years. Next is to become a better writer. Throughout junior college, writing has always been my weakest point and with the amount of writing assignments required at University of Phoenix this needs to be one of my top goals. Finally is to complete every course with no less than a B letter grade. With making the decision to return to school and taking on the considerable financial burden, receiving an average grade would be unacceptable to my standards.   Ã‚  Ã‚  Ã‚  Ã‚  While being employed full-time, The University of Phoenix has the rare opportunity for working professionals to finish courses in just 5 weeks. Having such a compressed time schedule for completing degrees will make it possible to complete my bachelor of science in business management in 2 years as long as I do not deviate from the program. I have decided that my number one priority in life is to complete my degree. I do not have other major commitments outside of work that will distract me from my assignments so staying focused on school will be realistic. Though I cannot predict the future, I do not plan on taking any time off during the two years that would result in interrupting my class schedule. With the option of taking CLEP test this will allow me to â€Å"test out† of some of the lower-division courses such as communication arts and humanities. Although this will require additional studying outside of my upper-division courses the CLEP test can hel p eliminate additional courses needed to be taken, so I can stay on track of my 2 year goal.   Ã‚  Ã‚  Ã‚  Ã‚  Writing papers has never been my strongest asset throughout school. I always found myself only writing what was required of me but never trying to improve my writing skills on my own time. In junior college the majority of my classes were math and science with a major in Administration of Justice. The only writing that I had to do was case briefs, which was based on legal research, which did not require any creativity, brainstorming and writing skills, just citing the facts and decisions in a proper format. To become a better writer it will take self-discipline and dedication. Because writing is my weakest point, submitting quality papers will require the most amount of my time by doing research and proofreading.

Earth Science Essay

Stars are one of the celestial bodies found in the solar system. Such celestial object produces heat, light, and different forms of radiations such as x-rays and ultraviolet rays caused by its cosmic energy engines. All stars are made up of gas, plasma, and matters comprised of subatomic particles that are extremely heated. From the earth, it may appear that stars are near because of their radiance shining over. However, stars are very far away that most of the scientists have to develop methods in order to calculate their distance. Two of the most notable methods are the parallax technique and the use of Cepheid variable (National Geographic, 2008). The parallax technique is used in order to identify the distance of the stars that are closest to the earth. Due to the revolution of the earth to the sun, the stars that are near to the earth shifts position against the stars that are in farther positions. These changes in the position of the nearby stars are known as the parallax shift. The parallax method functions by observing the distance of the shifting process and determining the earth’s orbit diameter. From there, astronomers are able to determine the parallax angle of the star’s distance. The main principle behind the method is that â€Å"the smaller the parallax shift, the farther away the star is from the earth† (Windows to the Universe Team, 2000, n. p. ). Such method is only applicable for stars that are within the range of few hundred light years from earth. Thus, when stars exceed the given range, the parallax shift could be too small to be measured through this technique (Windows to the Universe Team, 2000). For the countless distant stars that are in the range beyond 100 light years and are in clusters found in a different galaxy, the measurement is identified through the star’s property known as Cepheid variable. Stars that have this property undergo a fixed cycle where they get brighter and dimmer. This property is common among stars that are in â€Å"old age† (Berger, 2002, n. p. ). Because of their abundance in space, astronomers measure their distance by determining the number of cycle when stars are bright (Berger, 2002). There are many ways to measure the distance of the stars. It may be obtained from the stars spectral properties, temperature, brightness, and luminosity. Because of the major efforts in improving the measurements of the distances of the stars, various ways are also formulated in order to determine the cosmic distance of other celestial bodies present in the sky. References Berger, W. H. (2002). Measuring distance to the stars. In Intro to Astronomy: Discussion of the Field of Astronomy, University of California, San Diego. Retrieved September 17, 2008 from http://earthguide. ucsd. edu/virtualmuseum/ita/06_3. shtml. National Geographic. (2008). Stars. Retrieved September 17, 2008 from http://science. nationalgeographic. com/science/space/universe/stars-article. html Windows to the Universe Team. (2000, September). How do astronomers measure the distance to stars? Is it accurate? University Corporation For Atmospheric Research. Retrieved September 17, 2008 from http://www. windows. ucar. edu/tour/link=/kids_space/star_dist. html.

Facts on the Russo-Japanese War

The Russo-Japanese War of 1904-1905 pitted expansionist Russia against up-and-coming Japan. Russia sought warm-water ports and control of Manchuria, while Japan opposed them. Japan emerged as a naval power and Admiral Togo Heihachiro achieved international fame. Russia lost two of its three naval fleets. Snapshot of the Russo-Japanese War: When: February 8, 1904, to September 5, 1905Where: The Yellow Sea, Manchuria, the Korean PeninsulaWho: The Russian Empire, ruled by Tsar Nicholas II, versus the Japanese Empire, ruled by the Meiji Emperor Total Troop Deployment: Russia - approx. 2,000,000Japan - 400,000 Who won the Russo-Japanese War? Amazingly, the Japanese Empire defeated the Russian Empire, thanks mostly to superior naval strength and tactics. It was a negotiated peace, rather than a complete or crushing victory, but hugely important for Japans rising status in the world. Total Deaths: In battle - Russian, approx. 38,000; Japanese, 58,257.From disease - Russian, 18,830; Japanese, 21,802. (Source: Patrick W. Kelley, Military Preventive Medicine: Mobilization and Deployment, 2004) Major Events and Turning Points: Battle of Port Arthur, Feb. 8 - 9, 1904: This opening battle was fought by Japanese Admiral Togo Heihachiro against Russian Vice Admiral  Oskar Victorovich Stark in a surprise night attack by the Japanese. While the battle was largely inconclusive, it resulted in a formal declaration of war between Russia and Japan on the day after the battle.Battle of Yalu River, April 30 - May 1, 1904Siege of Port Arthur, July 30 - January 2, 1905Battle of the Yellow Sea, August 10, 1904Battle of Sandepu, January 25 - 29, 1905Battle of Mukden, February 20 - March 10, 1905Battle of Tsushima, May 27 -28, 1905: Admiral Togo destroyed a fleet of Russian ships, ambushing them on their way through the Tsushima Strait on their way to Vladivostok. After this victory, Russias prestige was damaged and they sued for peace.Treaty of Portsmouth, September 5, 1905, formally ended the Russo-Japanese. Signed at Portsmouth, Maine, USA. Theodore Roosevelt earned the Nobel Peace Prize for negotiating the treaty. Significance of the Russo-Japanese War The Russo-Japanese War held great international significance, as it was the first all-out war of the modern era in which a non-European power defeated one of Europes great powers. As a result, the Russian Empire and Tsar Nicholas II lost considerable prestige, along with two of their three naval fleets. Popular outrage in Russia at the outcome helped lead to the Russian Revolution of 1905, a wave of unrest that lasted more than two years but did not manage to topple the tsars government. For the Japanese Empire, of course, victory in the Russo-Japanese War cemented its place as an up-and-coming great power, particularly since it came on the heels of Japans victory in the First Sino-Japanese War of 1894-95. Nonetheless, public opinion in Japan was none too favorable. The Treaty of Portsmouth did not grant Japan either the territory or the monetary reparations that the Japanese people expected after their significant investment of energy and blood in the war.