6 MCQs in Statistics ...

  

(1) The best regression line is the one that:

Answer 

  

is furthest from the set of sample   data points.

 

has an S-shape.

 

maximizes the sum of the squared   errors.

 

minimizes the sum of the squared errors.

 

minimizes the coefficient of   determination r².

(2) Which of the following is a qualitative factor rather than a quantitative factor?

Answer 

  

Weekly sales for a company

 

New legislation

 

Total production cost

 

Gross national product

 

All of the above

     

(3) A consulting firm has received 2 Super Bowl playoff tickets from one of its clients. To be fair, the firm is randomly selecting two different employee names to 'win' the tickets. There are 6 secretaries, 5 consultants and 4 partners in the firm. Which of the following statements is not true?

Answer 

  

The probability of a secretary   winning a ticket on the first draw is 6/15.

 

The probability of a secretary winning a ticket on the second draw   given a consultant won a ticket on the first draw is 6/15.

 

The probability of a consultant   winning a ticket on the first draw is 1/3.

 

The probability of two secretaries   winning both tickets is 1/7.

(4) The efficiency of sample information is the ratio of the expected value of sample information to the:

Answer 

  

expected value of perfect information.

 

expected value.

 

utilization rate.

 

coefficient of optimism.

 

expected opportunity loss.

(5) Which of the following statements about scatter diagrams is true?

Answer 

  

Time is always plotted on the Y   axis.

 

It can depict the relationship   among three variables simultaneously.

 

It is helpful when forecasting   with qualitative data.

 

The variable to be forecasted is placed on the Y axis.

 

It is not a good tool for   understanding time-series data.

(6) The random error in a regression equation:

Answer 

  

is the predicted error.

 

includes both positive and negative terms.

 

will sum to a large positive   number.

 

is used the estimate the accuracy   of the slope.

 

is maximized in a least squares   regression model.