Ch3 Review

Researchers interested in the relationship between miles run by cross country runners during the week and their performance on race day collected data from randomly selected college athletes. The scatterplot displays the observed relationship.Which one of the following statements is true?

• Miles Run During Week should be on the vertical axis and Time on Race Day should be placed on the horizontal axis.
• A scatterplot is not appropriate for this data.
• The scatterplot is correct.

The scatterplot displays the relationship between the area of the seven continents and the population on each continent.Which of the following provides a correct description of the observed relationship?

• Smaller continents tend to have smaller populations.
• There does not appear to be any outliers.
• There is a very strong linear pattern.
• The relationship between area and population is negative.

A scatterplot displayed a roughly linear relationship between miles run per week in practice and the time required to finish a race for a random sample of 25 cross country runners from a recent meet. The correlation for this relationship was found to be –0.89. What is the interpretation of the correlation?

• There is not enough information to interpret the correlation.
• The linear relationship between miles run per week in practice and time to finish the race for these runners is weak and negative.
• The linear relationship between miles run per week in practice and time to finish the race for these runners is strong and positive.
• The linear relationship between miles run per week in practice and time to finish the race for these runners is strong and negative.

A cross-country runner collects data on his weekly practice and performance during races. He notices that the relationship between miles run the week before a race and his race time have a correlation of –0.97. Which of the following is an incorrect conclusion about the relationship between weekly practice and race performance?

• There is a strong relationship between miles run during the week and race time.
• There is a negative relationship between miles run during the week and race time.
• As the number of miles run during the week increase, his race times tend to decrease.
• An increase in miles run during the week causes his race time to decrease.

The table shows the age (measured in years) and weight (measured in kilograms) for a random sample of 5 children aged from birth to 18. Calculate the correlation for these data.Age1513161213Weight61.542.660.643.649.5

• 0.9
• –0.9
• –0.85
• 0.85

A politician wanted to know if there was a relationship between the amount of time he spent holding rallies in a city and the percent of votes he received from the voters in that city. A random sample of 9 cities were selected. The amount of time spent there (in days) as well as the percent of votes received from voters in that city are displayed in the scatterplot. The correlation between time and percent of votes is r = –0.121.Which of the following is correct?I.    If time was recorded in hours, rather than days, the correlation would be (–0.121)(24) = –2.904.II.   Plotting time on the vertical axis and percent of votes on the horizontal axis would not change the correlation.III. The correlation between time and percent of votes can be interpreted as –0.121 percent per day.

• I, II and III
• I and II
• II only
• I only

A student taking advanced math needed a more advanced calculator. Ebay.com had several auctions for the calculator. The time remaining in the auctions and the current bid price were recorded. Here is the scatterplot of the data, along with the equation of the regression line .What is the predicted bid price for a calculator with 40 minutes remaining?

• The price decreases $0.41 per hour, so we need to know how much time has passed (not how much time remains) in order to predict the price.
• The predicted bid price for a calculator with 40 minutes remaining on the auction is $52.38.
• The predicted bid price for a calculator with 40 minutes remaining on the auction is $68.51.
• The predicted bid price for a calculator with 40 minutes remaining on the auction is $68.78.

A student needed a calculator for her statistics class. She collected selling price and number of bids received from Ebay.com on the same model of calculator she needs to purchase. The equation of the regression line is where x = the number of bids received and = the predicted selling price. Calculate and interpret the residual for a calculator that received 6 bids and sold for $60.

• This calculator sold for $2.32 less than expected, based on the regression line using x = selling price.
• This calculator sold for $2.32 more than expected, based on the regression line using x = number of bids.
• This calculator sold for $2.32 less than expected, based on the regression line using x = number of bids.
• This calculator sold for $2.32 more than expected, based on the regression line using x = selling price.

Typically, the number of light fixtures built into a house has a relationship with the monthly electric bill. The scatterplot displays this relationship for a random selection of 13 homes that receive their electricity from a local energy company along with the least-squares regression line. The equation of the least-squares regression line is and the correlation is r = 0.811.Which of the following is correct?I.   The removal of the point in the upper right corner will decrease the correlation. II.  The predicted electric bill for a house with 60 electric fixtures is $192.20. III. The home with 8 light fixtures and an electric bill of $64 has a residual of –$21.53.

• I only
• II
• III only
• I, II and III

A student needed a calculator for statistics class. She collected selling price and bid data from Ebay.com on the same model of calculator she needs to purchase. The equation of the regression line is , where x = the number of bids and = the predicted selling price (in dollars). What is the interpretation of the slope and y intercept?

• The predicted selling price for a calculator increases by $60.386 for each additional bid. The y intercept has no meaning in this context.
• The selling price for a calculator increases by $0.322 for each additional bid. When there are no bids, the selling price for a calculator is $60.386.
• The predicted selling price for a calculator decreases by $0.322 for each additional bid. When there are no bids, the predicted selling price for a calculator is $60.386.
• The predicted selling price for a calculator increases by $0.322 for each additional bid. When there are no bids, the predicted selling price for a calculator is $60.386.