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zloy xaker [14]
3 years ago
5

A real estate builder wishes to determine how house size (House) is influenced by family income (Income), family size (Size), an

d education of the head of household (School). House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is in years. The builder randomly selected 50 families and ran the multiple regression. The business literature involving human capital shows that education influences an individual’s annual income. Combined, these may influence family size. With this in mind, what should the real estate builder be particularly concerned with when analyzing the multiple regression model? Question 7 options: Randomness of error terms Collinearity Missing observations Normality of residuals
Mathematics
1 answer:
Gnom [1K]3 years ago
8 0

Answer:

Multicollinearity

Step-by-step explanation:

Multicollinearity (also collinearity) is a phenomenon in which one predictor variable in a multiple regression model can be linearly predicted from the others with a substantial degree of accuracy. Also here we can see that variables to determine house sizes is family income which is correlated with the education level further combining both the factor we have another correlation with the family size, this phenomena where two or more predictors in a regression model are moderately or highly correlated is known as multicollinearity.

The basic problem is multicollinearity results in unstable parameter estimates which makes it very difficult to assess the effect of independent variables on dependent variables.

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System of equations <br> 5x+y=7<br> 20x+2=y
KIM [24]
Dependent

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----- (1)
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Comparing equations 1 and 2 with the general form of equation to write their co-efficient,

Compare the ratio,

If , then the pair of linear equations has exactly one solution.
So, it said to be consistent.
7 0
4 years ago
If 50 kg of rice cost Rs 375,how much can be purchased for Rs.525?​
uysha [10]

Answer:

70kg can be purchased for Rs 525

Step-by-step explanation:

Let the quantity of rice that can be bought with Rs 525 be = x

           Rice ( kg)                Cost (Rs)

              50                          375

                x                           525

  \frac{50}{x} = \frac{375}{525} \\\\x \times 375 = 50 \times 525\\\\375x = 26250\\\\x = \frac{26250}{375} = 70 \ kg

Therefore 70kg rice can be purchased for Rs. 525

8 0
3 years ago
A shop-keeper wants to charge 1.5 times
FrozenT [24]

Answer:

ok so the equation would look like this

B=1.5A

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7 0
3 years ago
Read 2 more answers
The tables show the years in which climbers on an expedition were born.
Amanda [17]
Part A

See the attached image to see how to form the double stem-and-leaf plot. Each leaf represents an individual data value. Specifically it is the year number (right-most single digit only). The stem is the rest of the year. The stem and leaf together combine to form the whole year.

For instance, the stem of 196 combined with the leaf of 4 represents the year 1964. This is shown on the image attachment. 

The leaf of '4', that is attached to the stem of 196, will go under the "did not reach the summit" column to indicate there was a failed attempt by someone born in 1964. In contrast, there is a successful attempt by someone born in 1973 for instance. So well write '3' next to the 197 in the "reached the summit" column. The rest of the values are sorted in this way. Again see the attached to get a good idea of what is going on.

=========================================

Part B

The shape of the distribution for those who reached the summit is fairly symmetrical. The center is around the decade of the 1960s or so. On either side of this center lays values that are fairly equal number. In other words, on the left side is the same amount as the right side. Imagine that the distribution has been tipped to rotate 90 degrees.

In contrast, the distribution for the people who didn't reach the summit is skewed to the left. The majority of the climbers who didn't reach the summit are clustered in the range of 1970 to 1990 or around there. The outliers earlier in the century (eg: 1939) pull the distribution to the left to give it a longer tail. This is why the distibution is skewed to the left. 

=========================================

Part C

Although the first two attempts ended in failure (1939, 1945), the next three were successful. The status of success or failure would then alternate heavily favoring the success column. Its mainly successes until we reach about 1970 is when the failures start to pile up. So in general there's mainly success at first (ignoring 1939 and 1945) that leads to failure later on. The cause of this swap isn't stated, but it's curious why this is. 

4 0
3 years ago
Which situation can be represented by the inequality 4x - 25_&lt; 125
Sav [38]
4x-25  \leq 125 \\ \\ 4x \leq 125+25 \\\\4x \leq 150 \\ \\ x \leq \frac{150}{4} \\ \\x \leq 37.5 \\\\ \boxed{x=(-\alpha;37.5]}
7 0
3 years ago
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