Week One

there be many similarities and many disparitys between pay back and correlativity coefficient. Causation is when one or more factors make for to an arrogate and correlativity is when both or more factors feed to one affect. An drill of causation is if I turn a gaffer on a threshold the door opens. correlational statistics coefficient is if a turn the knob on a door and unhook the bolt the door opens. When it comes to correlation there is two types, one is high correlation which is when the factors only stone up in a row to cause the effect, and low correlation when the results of one factor are scattered but a pattern shtup be made or accepted in it. The similarities between both causation and correlation are they both convey facts that point to a result. Te difference is that correlation is non causation because it means one factor go out not keep back an effect happen. Causation has a direct factor but correlation has many. W ealthy participation are abridge: This is an model of correlation because there is the interrogative why are wealthy people thin. not alone wealthy people are thin. Are they thin because they fucking afford a trainer and diet coach? there are many factors in this. People with long boar do better on adieu memory snap: This is an example of correlation. What makes the assumption of this? Is there test done on people with any types of hair?

Ice Cream Melts when heat up: This is an example of Causation. We all know ice melts when hot. Ice balm melts when hot it is a fact. Students with fewer garb perform worse on standardised tests: This is an ! example of Correlation. Why would a person with more vestments test better then some other with less? Who makes this decision? How do they know how much clothes each individual has? Money is the rote learning of all evil: Correlation I believe. Of course we can all say bullion is forefinger and people with power aim evil but not every person who has money is evil....If you want to get a full essay, rescript it on our website: OrderEssay.net

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