Prob Stat Review

How does the removal of a high outlier affect a distribution's mean?

• it increases the mean

• it decreases the mean

• it halves the mean

• the mean remains the same

What happens if you remove the outlier from the following dataset:

• the mean will increase

• the mean will decrease

• the mean will divide by 5 units

• the mean will remain the same

What letter do we use to represent correlation coefficient?

• c

• r

• p

• h

Describe the correlation in the graph shown.

• Strong Negative

• Strong Positive

• Weak Negative

• Weak Positive

The computer output below shows the result of a linear regression analysis for predicting the concentration of zinc, in parts per million (ppm), from the concentration of lead, in ppm, found in fish from a certain river. Which of the following statements is a correct interpretation of the value 19.0 in the output?

• On average there is a predicted increase of 19.0 ppm in concentration of lead for every increase of 1 ppm in concentration of zinc found in the fish.

• On average there is a predicted increase of 19.0 ppm in concentration of zinc for every increase of 1 ppm in concentration of lead found in the fish.

• The predicted concentration of zinc is 19.0 ppm in fish with no concentration of lead.

• The predicted concentration of lead is 19.0 ppm in fish with no concentration of zinc.

• Approximately 19% of the variability in the zinc concentration is predicted by its linear relationship with lead concentration.

The following computer output describes the relationship between y = height (in cm) and x = foot length (also in cm) for 12 randomly selected students from the British Census @ Schools database. The scatterplot for this relationship show a roughly linear shape. Which of the following is an equation of least-squares regression line for these data?

• Height = 117.99 + 1.878 (Foot Length)

• Foot Length = 117.99 + 1.878 (Height)

• Height = 1.878 + 117.99 (Foot Length)

• Foot Length = 1.878 + 117.99 (Height)

Is there a relationship between reaction time and age? A statistics student measures the reaction time of 12 subjects by measuring how far a yardstick drops, in inches, before a subject catches it between his or her thumb and forefinger (a high number thus indicates a slow reaction time). The student plans to use linear regression to see if reaction time can be predicted by the age of the subject. Output from a computer regression analysis is given below. The equation of the least-squares regression line is

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• 
• 

What is P(Not Blue Eyes and Wearing Yellow)? Hint: You need to simplify the fraction.

• 15/31

• 5/31

• 11/31

• 10/31

Which is NOT part of the Five Number Summary?

• mean

• median

• minimum

• maximum

• Q₁

What percent of all the data is between 50 and 70?

• 25%

• 33%

• 40%

• 50%