No. Since the data consist of ranks, it doesn't really make any sense to identify the sampling distribution of the sample means. If it was their scores in the triathlon, then it would have made some sense.

asked 2021-05-14

When σ is unknown and the sample size is \(\displaystyle{n}\geq{30}\), there are tow methods for computing confidence intervals for μμ. Method 1: Use the Student's t distribution with d.f. = n - 1. This is the method used in the text. It is widely employed in statistical studies. Also, most statistical software packages use this method. Method 2: When \(\displaystyle{n}\geq{30}\), use the sample standard deviation s as an estimate for σσ, and then use the standard normal distribution. This method is based on the fact that for large samples, s is a fairly good approximation for σσ. Also, for large n, the critical values for the Student's t distribution approach those of the standard normal distribution. Consider a random sample of size n = 31, with sample mean x¯=45.2 and sample standard deviation s = 5.3. (c) Compare intervals for the two methods. Would you say that confidence intervals using a Student's t distribution are more conservative in the sense that they tend to be longer than intervals based on the standard normal distribution?

asked 2021-04-13

As depicted in the applet, Albertine finds herself in a very odd contraption. She sits in a reclining chair, in front of a large, compressed spring. The spring is compressed 5.00 m from its equilibrium position, and a glass sits 19.8m from her outstretched foot.

a)Assuming that Albertine's mass is 60.0kg , what is \(\displaystyle\mu_{{k}}\), the coefficient of kinetic friction between the chair and the waxed floor? Use \(\displaystyle{g}={9.80}\frac{{m}}{{s}^{{2}}}\) for the magnitude of the acceleration due to gravity. Assume that the value of k found in Part A has three significant figures. Note that if you did not assume that k has three significant figures, it would be impossible to get three significant figures for \(\displaystyle\mu_{{k}}\), since the length scale along the bottom of the applet does not allow you to measure distances to that accuracy with different values of k.

a)Assuming that Albertine's mass is 60.0kg , what is \(\displaystyle\mu_{{k}}\), the coefficient of kinetic friction between the chair and the waxed floor? Use \(\displaystyle{g}={9.80}\frac{{m}}{{s}^{{2}}}\) for the magnitude of the acceleration due to gravity. Assume that the value of k found in Part A has three significant figures. Note that if you did not assume that k has three significant figures, it would be impossible to get three significant figures for \(\displaystyle\mu_{{k}}\), since the length scale along the bottom of the applet does not allow you to measure distances to that accuracy with different values of k.

asked 2021-05-21

When comparing two sets of data values, what is the advantage of using relative frequency distributions instead of frequency distributions?

asked 2021-05-22

Sheila is in Ms. Cai's class . She noticed that the graph of the perimeter for the "dented square" in problem 3-61 was a line . "I wonder what the graph of its area looks like ," she said to her teammates .

a. Write an equation for the area of the "dented square" if xx represents the length of the large square and yy represents the area of the square.

b. On graph paper , graph the rule you found for the area in part (a). Why does a 1st−quadrant graph make sense for this situation? Are there other values of xx that cannot work in this situation? Be sure to include an indication of this on your graph, as necessary.

c. Explain to Sheila what the graph of the area looks like.

d. Use the graph to approximate xx when the area of the shape is 20 square units.

a. Write an equation for the area of the "dented square" if xx represents the length of the large square and yy represents the area of the square.

b. On graph paper , graph the rule you found for the area in part (a). Why does a 1st−quadrant graph make sense for this situation? Are there other values of xx that cannot work in this situation? Be sure to include an indication of this on your graph, as necessary.

c. Explain to Sheila what the graph of the area looks like.

d. Use the graph to approximate xx when the area of the shape is 20 square units.

asked 2021-02-25

We will now add support for register-memory ALU operations to the classic five-stage RISC pipeline. To offset this increase in complexity, all memory addressing will be restricted to register indirect (i.e., all addresses are simply a value held in a register; no offset or displacement may be added to the register value). For example, the register-memory instruction add x4, x5, (x1) means add the contents of register x5 to the contents of the memory location with address equal to the value in register x1 and put the sum in register x4. Register-register ALU operations are unchanged. The following items apply to the integer RISC pipeline:

a. List a rearranged order of the five traditional stages of the RISC pipeline that will support register-memory operations implemented exclusively by register indirect addressing.

b. Describe what new forwarding paths are needed for the rearranged pipeline by stating the source, destination, and information transferred on each needed new path.

c. For the reordered stages of the RISC pipeline, what new data hazards are created by this addressing mode? Give an instruction sequence illustrating each new hazard.

d. List all of the ways that the RISC pipeline with register-memory ALU operations can have a different instruction count for a given program than the original RISC pipeline. Give a pair of specific instruction sequences, one for the original pipeline and one for the rearranged pipeline, to illustrate each way.

Hint for (d): Give a pair of instruction sequences where the RISC pipeline has “more” instructions than the reg-mem architecture. Also give a pair of instruction sequences where the RISC pipeline has “fewer” instructions than the reg-mem architecture.

a. List a rearranged order of the five traditional stages of the RISC pipeline that will support register-memory operations implemented exclusively by register indirect addressing.

b. Describe what new forwarding paths are needed for the rearranged pipeline by stating the source, destination, and information transferred on each needed new path.

c. For the reordered stages of the RISC pipeline, what new data hazards are created by this addressing mode? Give an instruction sequence illustrating each new hazard.

d. List all of the ways that the RISC pipeline with register-memory ALU operations can have a different instruction count for a given program than the original RISC pipeline. Give a pair of specific instruction sequences, one for the original pipeline and one for the rearranged pipeline, to illustrate each way.

Hint for (d): Give a pair of instruction sequences where the RISC pipeline has “more” instructions than the reg-mem architecture. Also give a pair of instruction sequences where the RISC pipeline has “fewer” instructions than the reg-mem architecture.

asked 2020-12-24

True or False

1.The goal of descriptive statistics is to simplify, summarize, and organize data.

2.A summary value, usually numerical, that describes a sample is called a parameter.

3.A researcher records the average age for a group of 25 preschool children selected to participate in a research study. The average age is an example of a statistic.

4.The median is the most commonly used measure of central tendency.

5.The mode is the best way to measure central tendency for data from a nominal scale of measurement.

6.A distribution of scores and a mean of 55 and a standard deviation of 4. The variance for this distribution is 16.

7.In a distribution with a mean of M = 36 and a standard deviation of SD = 8, a score of 40 would be considered an extreme value.

8.In a distribution with a mean of M = 76 and a standard deviation of SD = 7, a score of 91 would be considered an extreme value.

9.A negative correlation means that as the X values decrease, the Y values also tend to decrease.

10.The goal of a hypothesis test is to demonstrate that the patterns observed in the sample data represent real patterns in the population and are not simply due to chance or sampling error.

1.The goal of descriptive statistics is to simplify, summarize, and organize data.

2.A summary value, usually numerical, that describes a sample is called a parameter.

3.A researcher records the average age for a group of 25 preschool children selected to participate in a research study. The average age is an example of a statistic.

4.The median is the most commonly used measure of central tendency.

5.The mode is the best way to measure central tendency for data from a nominal scale of measurement.

6.A distribution of scores and a mean of 55 and a standard deviation of 4. The variance for this distribution is 16.

7.In a distribution with a mean of M = 36 and a standard deviation of SD = 8, a score of 40 would be considered an extreme value.

8.In a distribution with a mean of M = 76 and a standard deviation of SD = 7, a score of 91 would be considered an extreme value.

9.A negative correlation means that as the X values decrease, the Y values also tend to decrease.

10.The goal of a hypothesis test is to demonstrate that the patterns observed in the sample data represent real patterns in the population and are not simply due to chance or sampling error.

asked 2021-02-19

The distribution of height for a certain population of women is approximately normal with mean 65 inches and standard deviation 3.5 inches. Consider two different random samples taken from the population, one of size 5 and one of size 85.

Which of the following is true about the sampling distributions of the sample mean for the two sample sizes?

Both distributions are approximately normal with mean 65 and standard deviation 3.5.

A

Both distributions are approximately normal. The mean and standard deviation for size 5 are both less than the mean and standard deviation for size 85.

B

Both distributions are approximately normal with the same mean. The standard deviation for size 5 is greater than that for size 85.

C

Only the distribution for size 85 is approximately normal. Both distributions have mean 65 and standard deviation 3.5.

D

Only the distribution for size 85 is approximately normal. The mean and standard deviation for size 5 are both less than the mean and standard deviation for size 85.

E

Which of the following is true about the sampling distributions of the sample mean for the two sample sizes?

Both distributions are approximately normal with mean 65 and standard deviation 3.5.

A

Both distributions are approximately normal. The mean and standard deviation for size 5 are both less than the mean and standard deviation for size 85.

B

Both distributions are approximately normal with the same mean. The standard deviation for size 5 is greater than that for size 85.

C

Only the distribution for size 85 is approximately normal. Both distributions have mean 65 and standard deviation 3.5.

D

Only the distribution for size 85 is approximately normal. The mean and standard deviation for size 5 are both less than the mean and standard deviation for size 85.

E

asked 2021-06-13

Describe how to use random numbers to simulate the following PERFORMANCES:

(a) A basketball player has the ABILITY to make 40% of his shots and he takes 25 shots in a game.

(b) A basketball player has the ABILITY to make 75.2% of her free-throws and she takes 8 free throws in a game.

(a) A basketball player has the ABILITY to make 40% of his shots and he takes 25 shots in a game.

(b) A basketball player has the ABILITY to make 75.2% of her free-throws and she takes 8 free throws in a game.

asked 2021-03-09

Which of the following is true about the sampling distribution of means?

A. Shape of the sampling distribution of means is always the same shape as the population distribution, no matter what the sample size is.

B. Sampling distributions of means are always nearly normal.

C. Sampling distributions of means get closer to normality as the sample size increases.

D. Sampling distribution of the mean is always right skewed since means cannot be smaller than 0.

A. Shape of the sampling distribution of means is always the same shape as the population distribution, no matter what the sample size is.

B. Sampling distributions of means are always nearly normal.

C. Sampling distributions of means get closer to normality as the sample size increases.

D. Sampling distribution of the mean is always right skewed since means cannot be smaller than 0.

asked 2021-02-12

Which of the following is true about sampling distributions?

-Shape of the sampling distribution is always the same shape as the population distribution, no matter what the sample size is.

-Sampling distributions are always nearly normal.

-Sampling distribution of the mean is always right skewed since means cannot be smaller than 0.

-Sampling distributions get closer to normality as the sample size increases.

-Shape of the sampling distribution is always the same shape as the population distribution, no matter what the sample size is.

-Sampling distributions are always nearly normal.

-Sampling distribution of the mean is always right skewed since means cannot be smaller than 0.

-Sampling distributions get closer to normality as the sample size increases.