SECTION 4.2Complete the organizer for one-way analysis of variance. SSdfMSF-test Factors[A][B][C][D] Error[E][F][G]XXXXXXX Total[H][I]XXXXXXXXXXXXXX Although the context is unknown, the sum of squares for the factors or treatments is 196. The degrees of freedom for error is 11, the total sum of squares is 273, total degrees of freedom is 19, and the mean square error is 7. Test so to achieve 97% confidence with the results. **Question 9:**Is the *p*-value smaller than the level of significance, alpha or α?- No, the *p*-value is **much, much larger** than the level of significance.- No, the *p*-value is **larger** than the level of significance.- No, the *p*-value is **slightly or marginally larger** than the level of significance.- Yes, the *p*-value is **slightly or marginally smaller** than the level of significance.- Yes, the *p*-value is **smaller** than the level of significance.- Yes, the *p*-value is **much, much smaller** than the level of significance.**Question 10:**Which spreadsheet function generates the corresponding *p*-value, or the likelihood of the test statistic occurring? Let *x* represent the value of the test statistic you calculated.- a. =F.INV(*x*, df factors, df error)- b. =F.INV.RT(*x*, df factors, df error)- c. =F.DIST(*x*, df treatments, df error)- d. =F.DIST.RT(*x*, df treatments, df error)**Question 11:**Compute the corresponding *p*-value. Report the answer in decimal form, rounded to three decimal places following the decimal point.Ex: #.###**Question 12:**What is the most appropriate technical conclusion to draw from this hypothesis test?- Highly fail to reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.- Fail to reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.- Marginally fail to reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.- Marginally reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.- Reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.- Highly reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.

Solution: Given information: Sum of squares of treatments = SSTr= 196 The degrees of freedom for…

Answered: ECTION 4.2 Complete the organizer for…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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SECTION 4.2

Complete the organizer for one-way analysis of variance.


	SS	df	MS	F-test
Factors	[A]	[B]	[C]	[D]
Error	[E]	[F]	[G]	XXXXXXX
Total	[H]	[I]	XXXXXXX	XXXXXXX

Although the context is unknown, the sum of squares for the factors or treatments is 196. The degrees of freedom for error is 11, the total sum of squares is 273, total degrees of freedom is 19, and the mean square error is 7. Test so to achieve 97% confidence with the results.

**Question 9:**

Is the *p*-value smaller than the level of significance, alpha or α?

- No, the *p*-value is **much, much larger** than the level of significance.
- No, the *p*-value is **larger** than the level of significance.
- No, the *p*-value is **slightly or marginally larger** than the level of significance.
- Yes, the *p*-value is **slightly or marginally smaller** than the level of significance.
- Yes, the *p*-value is **smaller** than the level of significance.
- Yes, the *p*-value is **much, much smaller** than the level of significance.

**Question 10:**

Which spreadsheet function generates the corresponding *p*-value, or the likelihood of the test statistic occurring? Let *x* represent the value of the test statistic you calculated.

- a. =F.INV(*x*, df factors, df error)
- b. =F.INV.RT(*x*, df factors, df error)
- c. =F.DIST(*x*, df treatments, df error)
- d. =F.DIST.RT(*x*, df treatments, df error)

**Question 11:**

Compute the corresponding *p*-value. Report the answer in decimal form, rounded to three decimal places following the decimal point.

Ex: #.###

**Question 12:**

What is the most appropriate technical conclusion to draw from this hypothesis test?

- Highly fail to reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.
- Fail to reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.
- Marginally fail to reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.
- Marginally reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.
- Reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.
- Highly reject the null hypothesis, based on the available evidence and testing at the indicated level of significance.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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