Correct answer is C. Analysus of variance can be used to compare three treatments with continious data.

Question

asked 2021-06-13

1. The standard error of the estimate is the same at all points along the regression line because we assumed that
A. The observed values of y are normally distributed around each estimated value of y-hat.
B. The variance of the distributions around each possible value of y-hat is the same.
C. All available data were taken into account when the regression line was calculated.
D. The regression line minimized the sum of the squared errors.
E. None of the above.

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 2021-06-21

Source, df, SS, MS, F

A, 2, 5.3

B, 3, 9.1

AB, 6,

Error, 12, 24.5

Total, 23, 43.7

a. Fill in the missing items in the table.

b. Do the data provide sufficient evidence to indicate that factors A and B interact? Test using \(\alpha \alpha=.05\). What are the practical implications of your answer?

c. Do the data provide sufficient evidence to indicate that factors A and B affect the response variable x? Explain.

asked 2021-05-14

Consider the accompanying data on flexural strength (MPa) for concrete beams of a certain type.

\(\begin{array}{|c|c|}\hline 11.8 & 7.7 & 6.5 & 6 .8& 9.7 & 6.8 & 7.3 \\ \hline 7.9 & 9.7 & 8.7 & 8.1 & 8.5 & 6.3 & 7.0 \\ \hline 7.3 & 7.4 & 5.3 & 9.0 & 8.1 & 11.3 & 6.3 \\ \hline 7.2 & 7.7 & 7.8 & 11.6 & 10.7 & 7.0 \\ \hline \end{array}\)

a) Calculate a point estimate of the mean value of strength for the conceptual population of all beams manufactured in this fashion. \([Hint.\ ?x_{j}=219.5.]\) (Round your answer to three decimal places.)

MPa

State which estimator you used.

\(x\)

\(p?\)

\(\frac{s}{x}\)

\(s\)

\(\tilde{\chi}\)

b) Calculate a point estimate of the strength value that separates the weakest \(50\%\) of all such beams from the strongest \(50\%\).

MPa

State which estimator you used.

\(s\)

\(x\)

\(p?\)

\(\tilde{\chi}\)

\(\frac{s}{x}\)

c) Calculate a point estimate of the population standard deviation ?. \([Hint:\ ?x_{i}2 = 1859.53.]\) (Round your answer to three decimal places.)

MPa

Interpret this point estimate.

This estimate describes the linearity of the data.

This estimate describes the bias of the data.

This estimate describes the spread of the data.

This estimate describes the center of the data.

Which estimator did you use?

\(\tilde{\chi}\)

\(x\)

\(s\)

\(\frac{s}{x}\)

\(p?\)

d) Calculate a point estimate of the proportion of all such beams whose flexural strength exceeds 10 MPa. [Hint: Think of an observation as a "success" if it exceeds 10.] (Round your answer to three decimal places.)

e) Calculate a point estimate of the population coefficient of variation \(\frac{?}{?}\). (Round your answer to four decimal places.)

State which estimator you used.

\(p?\)

\(\tilde{\chi}\)

\(s\)

\(\frac{s}{x}\)

\(x\)

\(\begin{array}{|c|c|}\hline 11.8 & 7.7 & 6.5 & 6 .8& 9.7 & 6.8 & 7.3 \\ \hline 7.9 & 9.7 & 8.7 & 8.1 & 8.5 & 6.3 & 7.0 \\ \hline 7.3 & 7.4 & 5.3 & 9.0 & 8.1 & 11.3 & 6.3 \\ \hline 7.2 & 7.7 & 7.8 & 11.6 & 10.7 & 7.0 \\ \hline \end{array}\)

a) Calculate a point estimate of the mean value of strength for the conceptual population of all beams manufactured in this fashion. \([Hint.\ ?x_{j}=219.5.]\) (Round your answer to three decimal places.)

MPa

State which estimator you used.

\(x\)

\(p?\)

\(\frac{s}{x}\)

\(s\)

\(\tilde{\chi}\)

b) Calculate a point estimate of the strength value that separates the weakest \(50\%\) of all such beams from the strongest \(50\%\).

MPa

State which estimator you used.

\(s\)

\(x\)

\(p?\)

\(\tilde{\chi}\)

\(\frac{s}{x}\)

c) Calculate a point estimate of the population standard deviation ?. \([Hint:\ ?x_{i}2 = 1859.53.]\) (Round your answer to three decimal places.)

MPa

Interpret this point estimate.

This estimate describes the linearity of the data.

This estimate describes the bias of the data.

This estimate describes the spread of the data.

This estimate describes the center of the data.

Which estimator did you use?

\(\tilde{\chi}\)

\(x\)

\(s\)

\(\frac{s}{x}\)

\(p?\)

d) Calculate a point estimate of the proportion of all such beams whose flexural strength exceeds 10 MPa. [Hint: Think of an observation as a "success" if it exceeds 10.] (Round your answer to three decimal places.)

e) Calculate a point estimate of the population coefficient of variation \(\frac{?}{?}\). (Round your answer to four decimal places.)

State which estimator you used.

\(p?\)

\(\tilde{\chi}\)

\(s\)

\(\frac{s}{x}\)

\(x\)