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Which of the following is not one of the conditions that must be satisfied in order to perform inference about the slope of a least-squares regression line?

a. For each value of x, the population of y-values is Normally distributed.

b. The standard deviation 蟽 of the population of y-values corresponding to a given value of xis always the same, regardless of the specific value of x.

c. The sample size鈥攖hat is, the number of paired observations (x,y)鈥攅虫肠别别诲蝉 30.

d. There exists a straight line such that, for each value of x, the mean yof the corresponding population of y-values lies on that straight line.

e. The data come from a random sample or a randomized experiment.

Short Answer

Expert verified

Option (c) is the correct option.

Step by step solution

01

Step 1. Given information

a. For each value of x, the population of y-values is Normally distributed.

b. The standard deviation of the population of y-values corresponding to a given value of xis always the same, regardless of the specific value of x.

c. The sample size鈥攖hat is, the number of paired observations (x,y)鈥攅虫肠别别诲蝉 30.

d. There exists a straight line such that, for each value of x, the mean yof the corresponding population of y-values lies on that straight line.

e. The data come from a random sample or a randomized experiment.

02

Step 2. Explanation for correct option

Now, in the question we have to find out that which of these is not one of the conditions that must be satisfied in order to perform inference about the slope of a least-square regression line. Thus, we know that there are five conditions in order to perform inference about the slope of a least-squares regression line, that are: Random, Normal, Independent, Linear, Equal variance.

Thus, by looking at the options to get that:

Option (a) must be satisfied because it is the Normal requirement.

Option (b) must be satisfied because it is the Equal variance requirement.

Option (c) must not be satisfied because we require no limitations on the sample size.

Option (d) must be satisfied because it is the Linear requirement.

Option (e) must be satisfied because it is the Random requirement.

Thus, we have option (c) is not one of the condition that must be satisfied in order to perform inference about the slope of a least-square regression line.

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Most popular questions from this chapter

Determining tree biomass It is easy to measure the diameter at breast height (in centimeters) of a tree. It鈥檚 hard to measure the total aboveground biomass (in kilograms) of a tree because to do this, you must cut and weigh the tree. Biomass is important for studies of ecology, so ecologists commonly estimate it using a power model. The following figure is a scatterplot of the natural logarithm of biomass against the natural logarithm of diameter at breast height (DBH) for 378trees in tropical rain forests. The least-squares regression line for the transformed data is lny=-2.00+2.42lnxlny^=-2.00+2.42lnx^

Use this model to estimate the biomass of a tropical tree 30cm in diameter.

T12.9 Which of the following would provide evidence that a power model of the form y=axp, wherep0and p1, describes the relationship between a response variable y and an explanatory variable x?
a. A scatterplot of y versus x looks approximately linear.
b. A scatterplot of Iny versus x looks approximately linear.
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Do taller students require fewer steps to walk a fixed distance? The scatterplot shows the relationship between x=height (in inches) and y=number of steps required to walk the length of a school hallway for a random sample of 36 students at a high school.

A least-squares regression analysis was performed on the data. Here is some computer output from the analysis

Long legs Do these data provide convincing evidence at the =0.05level that taller students at this school require fewer steps to walk a fixed distance? Assume that the conditions for inference are met.

Do taller students require fewer steps to walk a fixed distance? The scatterplot shows the relationship between x=height (in inches) and y=number of steps required to walk the length of a school hallway for a random sample of 36 students at a high school.

A least-squares regression analysis was performed on the data. Here is some computer output from the analysis

a. Describe what the scatterplot tells you about the relationship between height and the number of steps.

b. What is the equation of the least-squares regression line? Define any variables you use.

c. Identify the value of each of the following from the computer output. Then provide an interpretation of each value.

i.b0

ii. b1

iii. s

iv.SEb1

Exercises T12.4鈥揟12.8 refer to the following setting. An old saying in golf is 鈥淵ou drive for show and you putt for dough.鈥 The point is that good putting is more important than long driving for shooting low scores and hence winning money. To see if this is the case, data from a random sample of 69 of the nearly 1000 players on the PGA Tour鈥檚 world money list are examined. The average number of putts per hole (fewer is better) and the player鈥檚 total winnings for the previous season are recorded and a least-squares regression line was fitted to the data. Assume the conditions for inference about the slope are met. Here is computer output from the regression analysis:

T12.7 Which of the following is the 95% confidence interval for the slope 尾1 of the population regression line?
a. 7,897,1793,023,782
b. 7,897,1792.000(3,023,782)
c. 4,139,1981,698,371
d. 4,139,1981.960(1,698,371)
e. 4,139,1982.000(1,698,371)

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