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Chapter 12: Q. AP4.2 (page 827)
If and P(B)=0.52 and events A and B are independent, what is P(A or B)?
a. 0.1248
b. 0.28
c. 0.6352
d. 0.76
e. The answer cannot be determined from the given information.
The P(A or B) is 0.76
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A random sample of students at a very large university was asked which social networking site they used most often during a typical week. Their responses are shown Page Number: in the table
Assuming that gender and preferred networking site are independent, how many females do you expect to choose LinkedIn?
a.
b.
c.
d.
e.
Multiple Choice Select the best answer for Exercises 23-28. Exercises 23-28 refer to the following setting. To see if students with longer feet tend to be taller, a random sample of students was selected from a large high school. For each student, ere recorded. We checked that the conditions for inference about the slope of the population regression line are met. Here is a portion of the computer output from a least-squares regression analysis using these data:
26. Which of the following is the best interpretation of the value in the computer output?
a. For each increase of in foot length, the average height increases by about
b. When using this model to predict height, the predictions will typically be off by about .
c. The linear relationship between foot length and height accounts for of the variation in height.
d. The linear relationship between foot length and height is moderate and positive.
e. In repeated samples of size the slope of the sample regression line for predicting height from foot length will typically vary from the population slope by about .
Killing bacteria Expose marine bacteria to X-rays for time periods from to minutes. Here is a scatterplot showing the number of surviving bacteria (in hundreds) on a culture plate after each exposure time:
a. Below is a scatterplot of the natural logarithm of the number of surviving bacteria versus time. Based on this graph, explain why it would be reasonable to use an exponential model to describe the relationship between the count of bacteria and the time.
b). Here is the output from a linear regression analysis of the transformed data. Give the equation of the least-squares regression line. Be sure to defne any variables you use.
c. Use your model to predict the number of surviving bacteria after minutes.
Braking distance How is the braking distance for a motorcycle related to the speed at which the motorcycle was traveling when the brake was applied? Statistics teacher Aaron Waggoner gathered data to answer this question. The table shows the speed (in miles per hour) and the distance needed to come to a complete stop when the brake was applied (in feet).
a. Transform both variables using logarithms. Then calculate and state the least-squares regression line using the transformed variables.
b. Use the model from part (a) to calculate and interpret the residual for the trial when the motorcycle was traveling at mph.
Students in Mr. Handford’s class dropped a kickball beneath a motion detector. The detector recorded the height of the ball (in feet) as it bounced up and down several times. Here is a computer output from a linear regression analysis of the transformed data of log(height) versus bounce number. Predict the highest point the ball reaches on its seventh bounce.
a. feet
b. feet
c. feet
d. feet
e. feet
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