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Geometro121 Geometro121
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Posts: 343
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A year ago
Which of the following is not an assumption for the simple linear regression model?
 a. The distribution of the error terms will be skewed to left or right depending on the values of the dependent variable.
  b. The error terms have equal variances for all values of the independent variable.
  c. The error terms are independent of each other.
  d. The mean of the dependent variable for all levels of the independent variable can be connected by a straight line.
  e. None of these.

Q. 2

A measure of how well an estimated regression line fits the sample data on which it is based, denoted by r2 (and equal to the proportion of the total variation in the values of the dependent variable, y, that can be explained by the association of y with x as measured by the estimated regression line) is known as:
 a. the sample coefficient of variation
  b. the sample of coefficient of correlation
  c. the sample coefficient of determination
  d. the sample coefficient of non-determination
  e. none of these

Q. 3

In regression analysis, if the values of the dependent variable, y, decrease with larger values of the independent variable, x, the variables are said to have:
 a. a direct relationship
  b. a nonsense correlation
  c. a deterministic relationship
  d. none of these

Q. 4

In (all types of) regression analysis, a variable whose value is known and is being used to explain or predict the value of another variable is called:
 a. an independent variable
  b. a predicted variable
  c. a dependent variable
  d. a response variable
  e. all of these

Q. 5

A regression analysis between weight (y in pounds) and height (x in inches) resulted in the following least squares line: y = 128 + 6x. This implies that if the height is increased by 1 inch, the weight on average is expected to:
 a. increase by 1 pound
  b. decrease by 1 pound
  c. increase by 6 pounds
  d. decrease by 6 pounds
  e. increase by 134 pounds

Q. 6

In a simple linear regression problem, suppose the sum of squares for regression (SSR) is 90 . Which of the following must be true?
 a. The correlation coefficient is 0.9.
  b. The coefficient of determination is 0.81.
  c. The total sum of squares (Total SS) is at least 90.
  d. The sum of squares for error (SSE) is at most 90.
  e. The coefficient of determination is 90.

Q. 7

For the values of the coefficient of determination listed below, which one yields the greatest value of sum of squares for regression given that the total sum of squares is 200?
 a. 0.90
  b. -0.90
  c. 0.00
  d. 0.98
  e. -0.98
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Answer verified by a subject expert
krakskraks
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Posts: 393
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A year ago
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Answer to #1

A

Answer to #2

C

Answer to #3

D

Answer to #4

A

Answer to #5

C

Answer to #6

C

Answer to #7

D
1

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