Final Stat Quiz
Ms. Kreppel is interested in the relationship between her students' final exam scores and their scores on a pre-test they took at the beginning of the year. A scatterplot of the data for the 18 students in her class shows linear relationship for these variables. The equation of the least squares regression line is Final Exam 34.2 0.60 Pre-test . One student scored a 76 on the pre-test and an 82 on the final exam. Which of the following is that student's residual?
2.2
A sociologist studying the relationship between early childhood nutrition and academic achievement in middle school among children in a certain city finds that the correlation between these two variables is 0.86. Which of the following conclusions can he draw from this study?
Children in this city who have a healthy diet in early childhood tend to do better in middle school.
A sociologist is studying the relationship between early childhood nutrition and academic achievement in middle school among children in a certain city. Which of the following statements about the variable "early childhood nutrition" is correct?
Early childhood nutrition is an explanatory variable.
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
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 the correct interpretation of the number s = 7.39858?
If we use the regression equation to predict height from foot length, our predictions will be, on average, off by 7.39858 centimeters.
Which of the following statements about the slope of the least-squares regression line is true?
It has the same sign as the correlation coefficient r.
A residual plot displays a "reverse fan" arrangement, with the spread of points about the line (residual = 0) gradually decreasing from left to right (that is, as x increases). Which statement would be a correct interpretation of this plot?
Predictions using the regression line will be more reliable for large x than for small x
One of the following is a correct statement involving correlation. The other two contain blunders. Which one is correct?
The correlation between amount of fertilizer and yield of tomatoes was found to be r = 0.33.
Ms. Kreppel is interested in the relationship between her students' final exam scores and their scores on a pre-test they took at the beginning of the year. Below is a scatterplot showing this relationship for the 18 students in her class. How would the slope of the least-squares regression line change if the individual whose point is circled were removed from the data set?
The slope would increase.
Which of the following quantities is minimized by the least-squares regression line?
The sum of the squared differences between observed values of the response variable and values of the response variable predicted by the model.
The following scatterplot describe the relationship between height (in cm) and foot length (also in cm) for 12 randomly selected students from the British Census @ Schools database. Which of the following is the best description of this relationship?
There is a moderately weak, positive linear relationship between height and foot length.
The points in the scatterplot represent paired observations (x, y) where x is an individual's weight and y is the time (in seconds) it takes for walking on a treadmill to raise the individual's pulse rate to 140 beats per minute. The open circles correspond to females and the dark squares to males.From the scatterplot, which conclusion we can make?
There is a negative correlation r between weight and time for both males and females.
Below is a residual plot for the regression of the number of employees of Microsoft Inc. on year for the years from 1976 to 1989. (Note that this is a residual plot, not a scatterplot!) There is no observed value for the year 1983. If we were to use this regression to predict the number of employees in 1983, which of the following is most likely to describe the accuracy of our prediction?
Too high
A study showed that students who spend more time studying for statistics tests tend to achieve better scores on their tests. In fact, the number of hours studied turned out to explain 81% of the observed variation in test scores among the students who participated in the study. What is the value of the correlation between number of hours studied and test score?
r = 0.9
