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Hi, my name is Budi. I will be your MAA SL teacher. I have been teaching since 2004 and I am honored to be a part of the member of the GJS. Still, I have lots of things to learn about education until now. To relieve my stress, I am taking care stray cats that surround my house. I hope we could work together well this year and I am looking forward to meeting you all.

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Hello my name is Hyun Woo

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Hi, my name is Eins. I've been in GJS since year 7. I like writing travel stories and travelling.

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Hi, my names is Joesph. I got to global jaya last year. I like to play football.

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I'm Vizenthe and I have been in global jaya all the way from kindergarten. I like trigonometry among other subjects, and I hope I can keep developing my  knowledge on various maths topics.

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I like maths but i'm not that good at it, hope I can learn lots in this class :D

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Hello my name is Naufal, I've been in Global Jaya since Year 7. I am not so good in maths but not that bad. I am able to achieve high scores but inconsistently. My favorite topic is geometry and trigonometry.

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I've been in Global Jaya since Year 6. I enjoy playing volleyball and football. I plan on applying to Engineering in the US.

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Helo my name is Rizqy and I've been in Global Jaya since Yr7

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But maybe a 5?

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Hello my name is Beebee (or Bianca, but calling me by my actual name makes me think you're mad so I go by Beebee). I have been in Global Jaya since year 6. I am aiming to become an engineer when I grow up, so I'm taking MAA SL along with Chemistry and Physics to support my aspirations. I have a cute 10 year old German Shepherd named Spike and a love for candies and sweets (so I may be a bit hyper in some classes). I like debating, studying and watching Anime. Nice to meet you, pak!

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Maybe a 7 if I pray a lot

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Learning new topics like statistics and calculus deeply and applying it to IA

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Id like to stop getting threes on all my tests.

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Selection bias is general conclusion from a specific population.

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To maintain academic success throughout all of the topics.

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I will aim to achieve solid 7

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I expect to achieve at least a 5 but a 6 is what I am aiming for.

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+ Getting consistent grade.
+ Fun and interactive learning strategies.
+Better timing during tests
+Limiting carelessness in calculation

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To be more hardworking and diligent

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I expect to get a average report grade of 5, but I am dreaming of getting a 6 even a 7 if I work really hard.

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To be more focused during classes and maintain my concentration levels during tests.

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Diligence in studying and production quality in IA-creating.

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I would like to be more careful with my working (cause I often miss points through really stupid mistakes) and practice on my application skills.

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I would like to be more disciplined in class and be more diligent so that I can make my expectations and hopes for this class come true.

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My expectation is a 4 maybe if im really lucky a 5.

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I am aiming for a 7 and can hopefully get a solid grade this semester (so at least 10% above the boundary just in case it changes)

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selection bias do not (failed to) represent the whole population

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Selection bias is an inaccurate conclusion taken from a data, caused by irrelevant sampling sizes or by too specific or small of a geographic area that it cannot accurately represent the preferences and traits of a wider demographic.

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A bias related to the selection of individuals/data sources such that the results are not representative of the intended population.

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Selection bias can lead to invalid conclusion because the data taken from one particular group are not similar or have equal size with the other group taken as a sample.

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How statistics can be misleading - Mark Liddell

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It is because same sets of data can be appeared to have the opposite trends depending on the way they are grouped - influenced by lurking variables.

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The context of a scenario will determine what way to view the data is most appropriate. Data can lead to very different conclusions which may or not support a certain agenda, making a study bias and unreliable. (yea the Simpson's Paradox)

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Selection bias is a sample investigated on does not represent the population that is being intended to be analyzed on.

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Collected data is linked to the validity of data because it affects the conclusions that can be made. The validity of data in the context of the investigation is jeopardized when it represents a general population misleadingly. This selection bias can either derive from choices made in sampling (e.g. not randomized/inappropriate demographics) or events occurring after that changed the makeup of the intended data (e.g. certain data points omitted, participants leaving midway).

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Selection bias is data collected that does not properly or accurately represent the targeted whole population which leads to an invalid conclusion.

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The collected data corresponds to what conclusions can be derived. Therefore, to ensure that the data is valid, the data collection must be accurate and not bias towards one sample. If there is bias sample, the data would be invalid.

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The data collected affects its validity depending on its size. For example, if we want to investigate how many people choose candidate A and candidate B in a presidential election, the size of the data collected determines the validity of the conclusion. If we only investigate the people in a city, the conclusion will not be as valid as investigating the people in a province, in order to reach the conclusion: which candidate has more voice.

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The data collection process and its validity are directly linked. When we conduct an investigation, we must make sure to minimize selection bias in that we collect data from a random group of people that effectively represents the traits of the intended demographic. By doing so, the data would be highly valid.

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There is a direct link between data collection and the validity of the data. This is because the method of data collection is crucial in determining an accurate, and a flaw such as selection bias can heavily influence the validity of the conclusion drawn from the study. Selection bias can greatly affect the validity data as it does not represent the whole population, as there can be several factors that affect how the sample is taken (only certain parts of a population, not randomized), meaning that the results will not represent the all of the population.

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The data collection can influence the validity of the data. If there is the selection bias in the data, it can affect the composition of the group (of data). further skewing the results.

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Because the same sets of data may reveal different conclusions depending on the specific breakdown or grouping of the data. In an aggregated data, there may be specific hidden factors that we must consider more than others in order to answer our specific questions.

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Selection bias is when the sample population does not accurately represent the entire targetted population

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The population from which data is collected and the method from which they are collected can affect the validity and reliability of the data. The conclusion drawn can vary greatly depending on how the data is interpreted which can determine its validity

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where the data is collected can affect the reliability/ validity of data.

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It is important to consider or define the context of the sampling to make sure that the conclusion drawn from the data are not biased or completely opposite due to some hidden variables or factors.

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Context gives a general idea of the scenario. Without context, the sample taken could have the potential to be irrelevant with what is intended. In addition, the context of a scenario allows all the variables and factors to be as accurate as possible.

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it is important to consider the context of a scenario in order to appropriate the sampling technique because different scenarios might have different facts that are relevant or irrelevant. As shown by the hospital example if it is comparing a hospital for elderly or infants but the infant hospital has higher survivability rate it would still make more sense to send the ill elderly to the elderly hospital.

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The context scenario is an important step that needs to be taken into consideration of when analyzing statistics as the data may lead to inaccurate and invalid results if the context is ignored. This is because there are hidden variables that can greatly view how we analyze statistics that greatly affect our conclusion of the presented data.

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To create a conclusion from the data, we need to understand the context of the sample so that the results are accurate and valid. There needs to be appropriate methods used in collecting the data corresponding to the context of it.

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Data: Objective facts and statistics (numbers), unbiased and raw
Information: Data processed to convey meaning in the "numbers"

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Bebeer, Aira, Hyun Woo, Eins, Naufal, Rizqy

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Bebeer, Aira, Hyun Woo, Eins, Naufal, Rizqy

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Data: Numerical and mostly used for analytical purposes. Unlike "information" it still needs to be processed (raw and unorganized)
Information: Group of data collected and processed to bring a logical meaning.