1. A dog groomer is often asked if small dogs bark more than larger dogs. To test this, he logs the number of separate barking episodes per day for three size dogs: small, medium, and large. Below is the number of barking episodes for 36 dogs.What are the independent and dependent variables in this study?On average, which size dog barked the most? Report the mean.On average, which size dog barked the least? Report the mean.Do the different size dogs bark a significantly different number of times? Test with an α = 0.05.If appropriate, use Tukey’s HSD post hoc test and report where the differences are. If inappropriate, state why.Calculate and interpret the effect size. MediumSmall8121410Large518.44210114438.496

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Description: 1. A dog groomer is often asked if small dogs bark more than larger dogs. To test this, he logs the number of separate barking episodes per day for three size dogs: small, medium, and large. Below is the number of barking episodes for 36 dogs.What ar

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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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1. A dog groomer is often asked if small dogs bark more than larger dogs. To test this, he logs the number of separate barking episodes per day for three size dogs: small, medium, and large. Below is the number of barking episodes for 36 dogs.

1. 1. What are the independent and dependent variables in this study?
  2. On average, which size dog barked the most? Report the mean.
  3. On average, which size dog barked the least? Report the mean.
  4. Do the different size dogs bark a significantly different number of times? Test with an α = 0.05.
  5. If appropriate, use Tukey’s HSD post hoc test and report where the differences are. If inappropriate, state why.
  6. Calculate and interpret the effect size.

Medium
Small
8
12
14
10
Large
5
1
8.
4
4
2
10
11
4
4
3
8.
4
9
6

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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