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2. An accountant for a small manufacturing plan t collected the following random sample to study the the selling price. Round all your relationship between x answers to one decimal place. cular item and y the cost to make a part 47 23 52 71 78 128 70 152 198 a. [4 pts] Create a scatter diagram. (2 pts] Using only the scatter diagram, would you estimate the correlation coefficient to be positive, close to zero, or negative? Explain your answer 4pts] Find the equation of the least squares line if the line crosses the y-axis at $7.7 and the ean point of this data set is (t,y) (44.8, 126.3). The standard deviations of x and y are $17.9 d $47.6, respectively.
[2 pts] Suppose that the cost to make a particular item is $35. What does the least-squares line predict as the selling price? e. [2 pts] Would you be able to predict the selling price for an item that cost $80 to be produced? f. [Extra-credit 4 pts] Graph the least squares line on your scatter plot. Mark it clearly. [3 pts] Joe and Maxine are playing a game where they flip a fair coin four times and try to predict the outcomes. Joe thinks that the probability of getting exactly two heads in the four flips is greater than the probability of getting heads on both the first and second flips. Maxine disagrees. She thinks that the two probabilities are equal. Who is correct, Joe or Maxine? The sample space of possible outcomes is listed below. H represents heads, and T represents tails. HHHH HHHT TTHT HTTH THHH TITT TTTH TTHH HTHH HTTT HHTT THTH HHTH THTT HTHT THHT
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Answer #1

2(a)

Scatterplot v vs x 250 200 1,198) 150 28) (50,132 (26,78) (23,70) 50 20 30 40 50 60 70 80 x($)

2(b)

It is seen that as x($) increases, y($) also increases. Thus it can be said that there is a positive correlation.

2(c)

The least square line is represented as

y = a + bx

where a=intercept on y-axis, b=slope

From the normal equations it is obtained that a = overline{y} - boverline{xoverline{}} => b = (overline{y}-a)/overline{xoverline{}}

From the problem it is given that a=7.7, overline{xoverline{}} =44.8,  overline{y}=126.3 => b = (126.3 - 7.7)/44.8 = 2.65

Therefore we get the least square line as

y = 7.7 + 2.65 x

2(d)

We get the least square line as y = 7.7 + 2.65 x

Now x = $35

Therefore y = $(7.7 + 2.65*35) = $100.45 approx $100.40

The least square line predicts the selling price of a particular item to be $100.40 when to cost to make it is $35.

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