Submitted By ivoryraaen33

Words 331

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Words 331

Pages 2

PSY/285

August 31, 2014

Causation and Correlation

Causation and correlation may seem like the same thing, but they are not. Causation is ‘caused’ by one or more factors or a combination of factors. Such as ice cream melting, ice cream is a frozen treat, being in a warmer environment will cause the ice cream to melt. Correlation is different from causation because correlation is the similarities or relationship between variables.

Correlation can be strong or weak, positive or negative. An example of correlation is people that are wealthy are thin. There really isn't any data to prove that wealthy people are always thin, but it can be based on money. One of the factors in this is that wealthy people can afford many different resources that will cause them to lose weight. Be it surgery, personal trainers, or expensive medical treatments, wealthy people can afford it and so they have the ability to change their appearance.

Another example of correlation is that people with fewer cloths perform worse on standardized tests than those with more cloths. Again there isn't any data that can successfully prove this theory one way or another, but it can be attributed to poverty. Students that live in poverty do worse than those that don’t because they don’t have the resources of those that don’t live in poverty.

They may also lack the education needed to pass standardized tests successfully. Whereas, students that don’t live in poverty have more resources and support.

People with longer hair do better on auditory test is correlation, because there isn't any data that can show that doing better on auditory tests in caused by having long hair. Money is the root of all evil. In other words…...

... 1. What does the correlation analysis study do? Explain with a numerical example. Deadline Tuesday 8pm. Answer: 1. Correlation Analysis Study gives us a medium for detecting and measuring the relationship between two variables. For instance: The table below shows the quantity of petrol consumed by each Salesman of a reputable pharmaceutical company along with the number of cartons (quantity) sold. 2. An independent variable is one that can be manipulated. In the equation y=f(x), y is considered as the dependent variable and x as the independent variable. For example; Resumption time at Work will be an independent variable where Volume of Traffic will be the dependent variable. In the example below Quantity Sold is the independent variable while Petrol consumed is the dependent variable. NDX | Salesman | Petrol Consumed (Litres) | Quantity Sold | 01 | A. J. Johnson | 50 | 200 | 02 | Peter Brown | 60 | 215 | 03 | T. Williams | 20 | 100 | 04 | S. Paulson | 60 | 250 | 05 | K. Okocha | 100 | 50 | 06 | T. Badoo | 25 | 120 | 07 | S. A. Brown | 7 | 30 | 08 | Saka Jojo | 60 | 300 | 09 | F. Dunka | 40 | 280 | 10 | K. Court | 50 | 280 | A direct observation of the data above shows a relationship between the petrol consumed by these salesmen and the quantity of products sold i.e. the more petrol used the higher the number of products sold. This may be generalistic though but it will be observed that some aberrations may be present for instance while K. Okocha......

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...What Is The Difference Between Causation and Correlation? The major discrepancy concerning causation and correlation is the power and measure to which two things are associated and the assurance with which anybody can institute a underlying relationship. Basically when you say one thing causes another, you are saying that there is a direct line between that one thing and the result. Cause means that an action will always have a predictable reaction. Once you describe correlation, the expressions cause and correlation grow to be easier to comprehend. If you see a correlation connecting two things, you can see that there is a affiliation between those two things. One thing does not automatically result in the other thing occurring, but it may increase likelihood that something will occur. The way to understand the difference of cause and correlation can best be understood by an example. For instance, “Violent video games cause violent behavior.” According to all research on this matter, this statement is not true, due to the use of the word causes in the sentence. Research has shown that violent video games may influence violent behavior. The correlation between violent video games and violent behavior some researchers have shown that there is a connection/correlation there. Violent games may influence others to act in more hostile but they are not the only reason and sometimes not even a factor for predicting violence. I believe that it really have a great impact on our...

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...Correlation Name: Institution: Correlation The main purpose of linear correlation is to show how strongly two variables affect each other. If the increase in one variable leads to no definite change in the other variable, we say that there is no correlation between the two variables. If the increase in one leads to the increase in the other, we say there is a positive correlation. However if the increase in one leads to a decrease in the other, there is negative correlation. The strength in of the relationship between two variables is show by the preciseness of the shift in one variable as the other increases. In a perfect linear correlation, all the points fall in a straight line. If the data however forms a straight vertical or horizontal line, there is no correlation as one variable has no effect on the other. An example of correlation in my daily life is the relationship studying and passing of exams. Students who study hard are more likely to pass as compared to those who do not. This does not mean a causality relationship as studying does not always result to high grades. Scientific methods involve the formulation of hypothesis, testing, and analyzing the results and formulating a new hypothesis based on the results. When trying to establish a causal relationship in the above example, one needs to be aware of the following factors. 1. The percentage of students who study hard for their exams. 2. The percentage of students who pass their......

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...Causation and Correlation Jennifer PSY/285 Darren Iwamoto July 17, 2013 Causation and Correlation Correlation does not imply causation. According to “statistical Language Correlation and Causation” (Correlation is a statistical measure (expressed as a number) that describes the size and direction of a relationship between two or more variables. A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable.) And (Causation indicates that one event is the result of the occurrence of the other event; i.e. there is a causal relationship between the two events. This is also referred to as cause and effect.) Causation and correlation can be difficult to discern from one another because they are so closely related to one another. Wealthy People are thin. Causation or correlation? The statement “Wealthy people are thin” is a correlation. Not all wealthy people are thin however there may be more thin wealthy people versus non wealthy people due to the fact that wealthy people can afford personal trainers, better food, and healthier lifestyles. People with long hair do better on audio memory tests. Causation or correlation? The statement “People with long hair do better on audio memory tests” is in fact a correlation, it is not a very strong correlation but it is indeed one. Ice cream melts when heated. Causation or correlation? The statement “Ice cream......

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...Difference Between Causation and Correlation Causation vs Correlation The two terms “causation” and “correlation” are usually interchanged, yet they are not interchangeable. Particular confusion arises in their understanding in the fields of health and scientific studies. EXAMPLE No 1: Every time we see a link between an event or action with another, what comes to mind is that the event or action has caused the other. This is not always so, linking one thing with another does not always prove that the result has been caused by the other. Causation Causation is an action or occurrence that can cause another. The result of an action is always predictable, providing a clear relation between them which can be established with certainty. Causation involves correlation which means that if an action causes another then they are correlated. The causation of these two correlated events or actions can be hard to establish but it is certain. Establishing causality between two correlated things has perplexed those that are involved in the health and pharmaceutical industries. The fact that an event or action causes another must be obvious and should be done with a controlled study between two groups of people. They must be from the same backgrounds and given two different experiences. The results are then compared and a conclusion can then be drawn from the outcome of the study. The process of observation plays a significant role in these studies as the subjects must be......

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...Think about how correlation is often miscast as causation. That is, cause is attributed to a variable when in fact, there is no causal relationship but only a correlation between the two variables. Consider any current news articles or media stories (especially political articles or stories) that involve correlations. The correlation is often miscast as causation, especially when political issues are taken into consideration. Recently the policy of President Obama health care services has been criticized tremendously. The correlation was miscast as causation. Describe how correlation might be interpreted inappropriately as causation. Also describe the possible explanations for the correlation. The Republicans claim the policy is ineffective because it led to the deterioration of the national health care system. This criticism replaces causation by correlation. What they fail to realize is that the President’s policy is not the cause of the problems we have with the health care system in this country. The deterioration of the national health care system is determined by multiple factors, which may be correlated and interdependent, such as the economic recession and the ineffective organization of the health care and insurance system. I would therefore say, President Obama’s policy on the health care system is an example of the case when correlation is replaced by causation. In actuality the current policy not the cause but is one of the factors that affects the......

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...Correlation November 21, 2011 How does a College basketball team make it to the finals or win a championship? Could it be the coach’s plays or is it the player’s defense techniques at obtaining rebounds. That is a question a coach may ask his players when giving a motivational speech before a game or during practices. Either solution or both can be a determinant. If the coach has plays that involve gaining rebounds then the plays and defense techniques can work together. Obtaining the ball after a missed shot gives that team another chance at making a shot to gain more points to win the game. The more rebounds you have the better chance you have at winning the game. In an effort to determine if there is a correlation between games won and the number of rebounds obtained each game, 50 college teams from the 2010/2011 school year were analyzed to see if a high number of rebounds had an effect on the teams that made it to the finals or won a championship title. After gathering the needed information from well-known resources, the information was put into the computer software program Minitab. Minitab calculated a variety of equations and the construction of a scatterplot graph that was used to conclude if there was a correlation between games won and rebounds. The scatterplot graph with the regression line showed a positive correlation between the games won and rebounds, as rebounds increased games won also increased. The upward slope indicated a positive value, but......

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...Correlation vs. Causation from the High- to the Late- Middle Ages (1000-1500) A comparative book review of Castles, Battles and Bombs: How Economics Explains Military History by Jurgen Brauer and Hubert van Tuyll and Battle: A History of Culture and Combat by John Lynn Nicole Campagnola 0774953 HIST*2040 (DE) W13 Professor Davison March 31, 2013 Despite proven facts and primary sources, historical investigation always has an element of subjectivity. Each historian has a different perspective, and focuses on different events and principles. Different historians and authors will often reflect upon the work of their peers, so an educated reader has the opportunity to decrease bias by expanding the list of sources that information comes from. Information that is accurately cited from appropriate sources does not always have a concrete and inarguable conclusion. There will always be differentiations based on the perspective that the author is striving to communicate, and the original intent behind their research. Castles, Battles and Bombs: How Economics Explains Military History by Jurgen Brauer (an economist) and Hubert van Tuyll (a historian) focuses on historical events with the foundation of economic principles, and uses these principles to explain past military decisions and strategies. Battle: A History of Culture and Combat by John Lynn argues that most historians have mistakenly defined styles of warfare and resulting successes based on......

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...Correlation and Causation The Link Between Sleep and Weight Correlation is the association between two variables, when there is an increase or decrease in one variable what effect does it has to the other variable (Triola, 2010). In this research the author looks on the relationship between a person who do not sleep or get quality sleep and their body weight. There was a study which highlighted a correlation between lack of sleep and increase in body weight. In the study with the women 40 – 60 years old, it was concluded that after studying their eating and sleeping pattern for 5-7 years women who had trouble falling asleep gained approximately 11 pounds. In the other study with the younger men, they studied their sleeping patterns for two consecutive days one day eight hour sleep and the other day four hour sleep. The researchers reported an increase in calorie intake (approximately 560 more) after sleeping for four days significantly more than the person who slept for eight hours. The two variables we have in this scenario is lack of sleep and increase in body weight, for these two variables to be correlated they must be linked or dependent on each other. Although the writer shows studies to show that when there is lack of sleep there is increase in appetite there can be other variables that determine the results such as location, body mass, individuals’ state of mind and age. According to the text the relationship between these two variables is weak and negative. The......

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...Correlation does not imply causation Almost daily we are in (mainly) news media whose owner has a structure similar to some of the following: One study claims that the more A, the more B A study says that those who are to have less B. A study says that since A is, then B is the other way. In principle, all these headlines indicate that basically what it says A is causing B to happen, or what is the same, that B is a consequence of A. Normally, when one reads the news, just realizing that so there is a correlation between A and B (come on, a relationship between these two events ), but in principle, without any indication that either one of them, even in this case, we cause the other B. (Oakes, 2012) The study of the correlation between two variables is one of the issues in question in Statistics. To summarize a bit, the question would be something like the following: - From certain data from each of these variables one estimates if there is any relationship between them. The one most frequently studied is called linear regression (by which we seek if there is no linear relationship between the variables), but there are many more possible types: quadratic, exponential, logarithmic... - With these data a function (which, for example, is a straight linear regression) that determines us exactly what the relationship between these variables is calculated. - The actual correlation between them is studied (ie, how strong is the relationship that we calculated based on the...

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...Business Statistics Topic: Correlation and Regression Recommended Readings: Lind D.A., Marchal W.G., and Wathen S.A. (2012), Statistical Techniques in Business and Economics, 15th International Ed., McGraw Hill [Chapter 13] Earlier edts are also suitable. Waters, D., (2008) Quantitative Methods for Business,4th Ed., Financial Times, Prentice Hall [Chapter 9] When we look at interval or ratio scale variables there is often a relationship, eg: price and quantity demanded; time spent studying and exam results obtained; gardai (police) on duty and number of crimes as well as alcohol consumed and sensibility! Regression and correlation analysis is useful because it allows us predict the value of one variable from the knowledge of another. The said relationship can be positive or negative. One first step in establishing if any of these relationships exist is to draw a scatter graph. A Scatter plot or diagram is a chart that portrays the relationship between the two variables. It is the usual first step in correlation analysis * The Dependent variable is the variable being predicted or estimated. * The Independent variable provides the basis for estimation. It is the predictor variable. Correlation Analysis From a scatter plot we have a first picture of the data. The next step is to calculate a measure which can assess the strength of that relationship. The correlation coefficient r which represents correlation in a sample is calculated as: r......

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...Part 1: Regression Descriptive Statistics| |Mean|Std. Deviation|N| Family income prior month, all sources|$1,485.49|$950.496|378| Hours worked per week in current job|33.52|12.359|378| Correlations| |Family income prior month, all sources|Hours worked per week in current job| Pearson Correlation|Family income prior month, all sources|1.000|.300| |Hours worked per week in current job|.300|1.000| Sig. (1-tailed)|Family income prior month, all sources|.|.000| |Hours worked per week in current job|.000|.| N|Family income prior month, all sources|378|378| |Hours worked per week in current job|378|378| Variables Entered/Removeda| Model|Variables Entered|Variables Removed|Method| 1|Hours worked per week in current jobb|.|Enter| a. Dependent Variable: Family income prior month, all sources| b. All requested variables entered.| Model Summary| Model|R|R Square|Adjusted R Square|Std. Error of the Estimate| 1|.300a|.090|.088|$907.877| a. Predictors: (Constant), Hours worked per week in current job| ANOVAa| Model|Sum of Squares|df|Mean Square|F|Sig.| 1|Regression|30683447.737|1|30683447.737|37.226|.000b| |Residual|309914616.753|376|824241.002||| |Total|340598064.489|377|||| a. Dependent Variable: Family income prior month, all sources| b. Predictors: (Constant), Hours worked per week in current job| Coefficientsa| Model|Unstandardized Coefficients|Standardized Coefficients|t|Sig.|95.0% Confidence Interval for B| |B|Std.......

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...------------------------------------------------- Causation and Correlation ------------------------------------------------- Courtney Clark July 19, 2015 psy/285 Taryn Stevenson July 19, 2015 psy/285 Taryn Stevenson 1. 2. 3. Home > 4. Health & Medicine > 5. Disease 6. > 7. Causation and Correlation 1. < Back to Health & Medicine Causation and Correlation Correlation does not imply causation * By missweetie * May 11, 2012 * 511 Words * 146 Views There are many similarities between causation and correlation but there are also just as many differences. Causation is when one or more factors contribute to the effect. As said in the PowerPoint review, for example, if you switch a light switch on it causes the light turns on. The one factor of flipping the light switch on causes the effect of the light to turn on. Correlation is when two or more factors contribute to one effect. There is two different types of correlation. One type of correlation is high correlation which is when the factors all match up in a row to cause the effect. Low correlation is when the results of one factor are scattered but a pattern can be recognized. The similarities between causation and correlation are that they both require factors that can point to a result. But remember that correlation is not causation. One factor does not mean it will make the effect happen. The difference between causation and......

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...The distinction between causation and correlation is very important in scientific thought. Oftentimes the two concepts get mixed up, sometimes out of a misunderstanding and other times due to a desire to provide a plausible explanation for a scientific observation. Therefore, it is very important to be able to understand the difference between the two ideas. Correlation is defined by Merriam-Webster’s online dictionary to be: “the state or relation of being correlated; specifically : a relation existing between phenomena or things or between mathematical or statistical variables which tend to vary, be associated, or occur together in a way not expected on the basis of chance alone “ In other words, a correlation is a relationship between two or more things which change (variables) that can be described mathematically. Correlation refers to how closely two sets of information or data are related. Wealthy people are thin This association is fickly being that not all wealthy people are thin. The ones who are thinner may have a nutritionist or diet is on a healthier side. They also may be on a regular workout. People with long hair do better on audio memory tests. This would be an association as well. No association between the two. Ice cream melts when heated. The association of these two goes together because when ice cream get to heat it melts so the two variables relate. Students with fewer clothes perform worse on standardized tests. There is no......

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...Introduction One of the problems linked with the assessment of research based on statistical analysis involves the determination of whether a true cause and effect connection between variables exists, or is it just a statistical relationship known as correlation. While there may be correlation between variables, there is not a causal relationship unless the variation in the independent variable or variables actually causes the variation in the dependent variable. Often correlation is misinterpreted as causation, as is the case in the examples presented in this essay. The first example is from a journal article that says watching TV increases a persons risk of heart disease and non-cancer related deaths. The second two examples are related to transportation, one saying that speeding causes car crashes and the other saying population in a traffic analysis zone (TAZ) causes trips produced. Although correlation is necessary it is not sufficient, it is important that a true causal relation exists before making conclusions. Body (Example A) The first study is presented in the journal, Circulation-Journal of the American Heart Association with the title, Television Viewing time and Mortality: The Australian Diabetes, Obesity and Lifestyle Study (AusDiab). The baseline data for the study was gathered between the years of 1999 and 2000. The locations for data collection were chosen based on Census Collector Districts in each of the Australian states and in the......

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