A researcher is interested to know whether the type of breakfast students consume has an effect on their test performance. Study participants were divided into three groups: 1) No breakfast before the test 2) Protein-only breakfast before the test 3) Carbs-only before the test Below are test results for each group. Conduct ANOVA in Google Sheets to determine if there are significant mean differences between any of the three groups. Assume alpha = 0.05 Copy/paste the data below into Google Sheets and perform ANOVA. Copy/paste the results in the response window below. Be sure to include your interpretation of the results. In your answer, state the null and the research hypotheses and explain whether the results of the ANOVA test led you to reject or fail to reject the null hypothesis. No breakfast Carbs Only Protein Only 85.79 82.42 77.59 68.95 84.70 54.73 68.01 91.92 76.90 62.24 94.23 86.10 73.82 91.55 82.50 70.90 83.51 81.84 82.30 95.82 93.42 68.77 93.87 90.66 80.63 82.18 77.61

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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A researcher is interested to know whether the type of breakfast students consume has an effect on their test performance.

Study participants were divided into three groups:

1) No breakfast before the test

2) Protein-only breakfast before the test

3) Carbs-only before the test

Below are test results for each group.

Conduct ANOVA in Google Sheets to determine if there are significant mean differences between any of the three groups.

Assume alpha = 0.05

Copy/paste the data below into Google Sheets and perform ANOVA.

Copy/paste the results in the response window below. Be sure to include your interpretation of the results. In your answer, state the null and the research hypotheses and explain whether the results of the ANOVA test led you to reject or fail to reject the null hypothesis.

No breakfast	Carbs Only	Protein Only
85.79	82.42	77.59
68.95	84.70	54.73
68.01	91.92	76.90
62.24	94.23	86.10
73.82	91.55	82.50
70.90	83.51	81.84
82.30	95.82	93.42
68.77	93.87	90.66
80.63	82.18	77.61

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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