Explanation Given: The data of 8 transactions, each webpage being regarded as a transaction. Formula used: If I a n d J are subsets of a set of transactions T , then, by definition, s u p p o r t ( I ⇒ J ) = c o u n t ( I ∪ J ) n u m b e r o f t r a n s a c t i o n s (3) c o n f i d e n c e ( I ⇒ J ) = c o u n t ( I ∪ J ) c o u n t ( I ) (4) Where c o u n t ( I ∪ J ) is the number of transactions that contain both I a n d J

Discrete Mathematics and Its Applications

8th Edition

ISBN: 9781260501759

Author: ROSEN

Publisher: MCG

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Chapter 9.2, Problem 36E

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The support and confidence of the association rule: {human,DNA}⇒{Neanderthal}

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Chapter 9.2, Problem 35E

Chapter 9.2, Problem 37E

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Suppose that a researcher, by using a sample of transactions of residential houses, wants to estimate how the price of the houses is affected by the absence of an elevator in the building. To this end, he regresses the price of the house in thousands euro, price, on the dummy no_elevator indicating the absence of the elevator (dummy equal to 1) or the presence (dummy equal to 0): price; = a0 +a1 no_elevator; + u; The OLS estimates are (standard errors in round brackets below the corresponding coefficient): R2 = 0.036 price; = 199.937 - 73.068 no_elevator; (10.735) (5.482) The poor fit of the model suggests the researcher to insert an additional regressor, namely the surface of the houses, area, in square meters. Supposing that area and no_elevator are negatively correlated, what do you think will happen to the previously estimated coefficient of no_elevator? O (a) We cannot say given the so poor fit of the model O (b) It will be larger than -73.068 (i.e. -30) O (c) It will be smaller…

Suppose that a researcher, by using a sample of transactions of residential houses, wants to estimate how the price of the houses is affected by the absence of an elevator in the building. To this end, he regresses the price of the house in thousands euro, price, on the dummy no_elevator indicating the absence of the elevator (dummy equal to 1) or the presence (dummy equal to 0): price; = a0 +a1 no_elevator; + u; The OLS estimates are (standard errors in round brackets below the corresponding coefficient): price; = 199.937 – 73.068 no_elevator; (5.482) R2 = 0.036 (10.735) Unfortunately, he makes an informatic mistake so that he uses the original dummy adding a value of 2, i.e. a variable that takes value 3 if there is not an elevator in the building and 2 if there is. How will the estimated value of the coefficients be affected by this mistake? O (a) The intercept will increase whereas the coefficient of the dummy will decrease O (b) The intercept will increase whereas the coefficient…

Using the 2^k less than or greater to rule, determine the number of classes needed for the following data set sizes. a) n=50 b) n=250 c) n=1500 d) n=3000

Chapter 9 Solutions

Discrete Mathematics and Its Applications

Ch. 9.1 - t the ordered pairs in the...Ch. 9.1 - a) List all the ordered pairs in the relation R =...Ch. 9.1 - each of these relations on the set {1, 2, 3, 4},...Ch. 9.1 - ermine whether the relationRon the set of all...Ch. 9.1 - ermine whether the relationRon the set of all Web...Ch. 9.1 - ermine whether the relationRon the set of all real...Ch. 9.1 - ermine whether the relationRon the set of all...Ch. 9.1 - w that the relationR=Oon a nonempty set S is...Ch. 9.1 - Show that the relationR=on the empty setS=is...Ch. 9.1 - e an example of a relation on a set that is a)...

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The support and confidence of the association rule: { h u m a n , D N A } ⇒ { N e a n d e r t h a l }

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To calculate:

The support and confidence of the association rule: {human,DNA}⇒{Neanderthal}