Tutor profile: Terrance C.
Assess the accuracy of the following statement: An atom of Hydrogen-1 undergoes alpha decay.
This is a common example of starting to apply your knowledge of a definition rather than simply repeating it. Let's recall some essential facts here... Alpha decay = a radioactive process involving the release of an alpha particle from a nucleus. The alpha particle is comprised of 2 protons and 2 neutrons. Hydrogen-1's nucleus is comprised of 1 proton because its atomic number is 1. There are 0 neutrons because the "Hydrogen-1" indicates a mass number (combined number of protons and neutrons) of 1, and there is already 1 proton present. Now it's time to combine your answers into a claim-evidence-reasoning format. Take a look at the samples below from the perspective of a college-level instructor. NO/LOW CREDIT: This statement is inaccurate because Hydrogen-1 cannot undergo alpha decay. Yes, the statement was inaccurate (Claim), but that explanation does not have any meaningful explanation (Evidence). There are no important facts or related information being used. PARTIAL CREDIT: This statement is inaccurate because the nucleus of Hydrogen-1 cannot contain alpha particles. This explanation is true (Claim and Evidence), but there's still some missing details that could make this answer more complete to show your reasoning! Otherwise, the instructor may need to guess if you actually understand this concept or not. FULL CREDIT: This statement is inaccurate because the nucleus of Hydrogen-1 cannot contain alpha particles. The reason is that alpha particles are made of 2 protons and 2 neutrons, but Hydrogen-1 contains only 1 proton. Yes, this is a lot to write out, but notice how this answer is written so that every important fact is explicitly stated. This added details show an instructor you know exactly how to answer this question and leaves no room for guessing whether or not you have mastered the material.
Subject: College Admissions
A common question that appears on many applications or essay prompts is "Why do you want to apply to ________?" What can you do to construct a strong response to this question?
HINT: Just saying "because I love _______" or "because I am passionate about attending ______" will not be an effective answer. This does not say anything unique about you, and admissions officers have probably read this response thousands of times! RESEARCH THE COLLEGE! I cannot stress this enough. Do not apply somewhere "just because it's a good school" or "because my parents say this program is #1 in the nation". Something that will show an admissions officer you truly want to be at their school is citing information from relevant school websites AND connecting that to your personal vision. Examples of information you could cite includes a school or department's mission statement or notable (and inspiring!) achievements. Take a look at the samples below... INEFFECTIVE: "I want to apply to _____ because its computer science program is top-ranked in the nation. This can help me become an extremely talented programmer who can change the world." Does this really say much about the writer? More importantly, does this sample strike you as unique or thought-provoking? Chances are, an admissions officer has probably read something like this statement many times and is tired of seeing it! EFFECTIVE: "I was inspired to apply to ______ in the computer science program after reflecting on its mission statement. Originally, I wanted to program out of personal interest, but realizing that computing has the power to change lives struck me, and I am now more deeply invested in learning about how to apply my skills to enact positive changes. Notice how this sample, while longer, manages to show an important aspect: growth. Here, the writer talks about their interests and also shows that they are proactive in more thoroughly learning about their prospective college. Of course, this sample will always vary based on each school's mission statement and how it specifically applies to you.
The marketing team for the game Fortnite conclude that number of golf carts appearing per game is related to player satisfaction and want to find the evidence using linear regression for 20 players. The independent variable X is the number of golf carts and the dependent variable Y is player satisfaction (on a percentage scale). Here are their following results... Y = 0.5X + 30 Coefficient of variation: 0.95 QUESTION: Provide a formal statistical analysis of the experimental results. BONUS: What is one criticism you might have for the team's statistical experiment?
ANSWER: Remember that linear regression equations follow the format Y = AX + B With A, the slope, representing the rate of change in Y relative to X and B, the y-intercept, representing a set amount of Y if X = 0. Therefore, this is what we should say... A slope of 0.5 suggests that for each golf cart added to the game, the player satisfaction increases by 0.5%. The y-intercept suggests that if there were no golf carts in the game, player satisfaction would be 30%. (Notice how I say suggests instead of concludes because this sample may not be a true representation of every single Fortnite player!) Furthermore, the coefficient of variation suggests that 95% of variation in player satisfaction can be explained by the amount of golf carts per game. BONUS: There are many things wrong with this experiment. I will point out two often incorrect assumptions. One is that the marketing team has made a conclusion BEFORE they found any evidence; a professional statistician will never make any solid conclusions unless they have equally strong evidence! Also, they are assuming that the relationship between the number of golf carts and player satisfaction is linear, which could cause them to miss some viable evidence. Don't forget that many other statistical relationships exist! (ex. exponential, logistic, etc.). For example, the data points may actually appear as an upside down parabola, showing that having too many golf carts will start decreasing player satisfaction! What else do you think could be improved in this experiment?
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