The times (in minutes) it took six white mice to learn to run a simple maze and the times it took six brown mice to run the same maze are recorded. Does the color of the mice make a significant difference in their learning rate? Use α=0.05.Based on the values, which mice (on the average) run faster?(Hint: Refer to the Mean Difference)WHITE, BROWN, OR NONE Independent Samples TestLevene's Testfor Equality ofVariancest-test for Equality of Means95% ConfidenceSig.Interval of theStd. Errortailed) Difference Difference Lower Upper(2-MeanDifferenceFSig.dfTime Equal variances.0052.77689 -5.85396 6.52063.945.12010.907.33333(W-B)assumedEqual variances1209.899.907.333332.77689-5.86250 6.52917not assumed

The appropriate conclusion regarding the claim is that if the learning time for both varieties of…

Answered: Independent Samples Test Levene's Test…

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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Question

The times (in minutes) it took six white mice to learn to run a simple maze and the times it took six brown mice to run the same maze are recorded. Does the color of the mice make a significant difference in their learning rate? Use α=0.05.

Based on the values, which mice (on the average) run faster?
(Hint: Refer to the Mean Difference)

WHITE, BROWN, OR NONE

Independent Samples Test
Levene's Test
for Equality of
Variances
t-test for Equality of Means
95% Confidence
Sig.
Interval of the
Std. Error
tailed) Difference Difference Lower Upper
(2-
Mean
Difference
F
Sig.
df
Time Equal variances
.005
2.77689 -5.85396 6.52063
.945
.120
10
.907
.33333
(W-B)
assumed
Equal variances
120
9.899
.907
.33333
2.77689
-5.86250 6.52917
not assumed

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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