Statistics in Real-World Contexts

A student recorded the following test scores for two classes. What is the mean score for Class A: 72, 85, 90, 68, 75?

• 76

• 78

• 80

• 74

Tags

GA.MA.9-12.A.DSR.10.1

A scatter plot shows the number of hours students studied and their exam scores. As the number of hours studied increases, the exam scores also increase. How would you describe the relationship between the two variables?

• No relationship

• Negative relationship

• Positive relationship

• Random relationship

Tags

GA.MA.9-12.A.DSR.10.3

A researcher finds that the correlation coefficient r = 0.95 between daily ice cream sales and the number of drowning incidents. What can be concluded?

• Eating ice cream causes drowning

• Drowning causes people to buy ice cream

• There is a strong correlation, but one does not cause the other

• There is no relationship between the two variables

Tags

GA.MA.9-12.A.DSR.10.7

The linear model for predicting a student's final exam score based on hours of study is y = 5x + 50. What does the intercept (50) represent in this context?

• The number of hours studied

• The predicted score when a student studies 5 hours

• The predicted final exam score when a student studies 0 hours

• The rate at which the score increases per hour

Tags

GA.MA.9-12.A.DSR.10.4

Which value of the correlation coefficient r indicates the strongest linear relationship between two variables?

• r = 0.25

• r = -0.95

• r = 0.50

• r = -0.10

Tags

GA.MA.9-12.A.DSR.10.5

Two basketball teams recorded their points per game over a season. Team A has a standard deviation of 8.2 points, and Team B has a standard deviation of 3.1 points. What does this tell us about the two teams?

• Team A scores more points on average than Team B

• Team B's scores are more consistent than Team A's scores

• Team A's scores are more consistent than Team B's scores

• Team B scores more points on average than Team A

Tags

GA.MA.9-12.A.DSR.10.1

A scatter plot is created using data on the age of a car (in years) and its resale value (in dollars). Which of the following best describes the expected relationship between these two variables?

• A positive linear relationship, because older cars are worth more

• A negative linear relationship, because older cars tend to be worth less

• No relationship, because age and value are unrelated

• A perfectly linear relationship with r = 1

Tags

GA.MA.9-12.A.DSR.10.3

A linear model for predicting monthly electricity bills (in dollars) based on average daily temperature (in °F) is given by y = 2.5x - 30. What does the slope of 2.5 mean in this context?

• The electricity bill decreases by $2.50 for every degree increase in temperature

• The electricity bill is $2.50 when the temperature is 0°F

• For every 1°F increase in temperature, the electricity bill increases by $2.50

• The electricity bill increases by $30 for every degree increase in temperature

Tags

GA.MA.9-12.A.DSR.10.4

A technology tool calculates the correlation coefficient for the relationship between the number of absences and final grades as r = -0.87. Which statement best interprets this value?

• There is a weak negative relationship between absences and final grades

• There is a strong negative relationship; students with more absences tend to have lower grades

• There is a strong positive relationship between absences and final grades

• Absences cause students to receive lower grades

Tags

GA.MA.9-12.A.DSR.10.5

A study finds a strong positive correlation (r = 0.91) between the number of fire trucks sent to a fire and the amount of damage caused. A city official concludes that sending more fire trucks causes more damage. What is wrong with this conclusion?

• The correlation coefficient is too low to draw any conclusion

• Correlation does not imply causation; larger fires require more trucks and also cause more damage

• The conclusion is correct because the correlation is strong

• The data should have been collected differently to support this conclusion

Tags

GA.MA.9-12.A.DSR.10.7