Use the dataset HT_4337.xls. Using Excel, conduct a t-test (at the alpha = 0.05 significance level) on whether the mean of X1 is equal to 100. What do you conclude from this sample data? Is the population mean equal to 100? Group of answer choices You cannot reject the null hypothesis. You conclude that the population mean is not equal to 100. You reject the null hypothesis. You conclude that the population mean is not equal to 100. You reject the null hypothesis. You conclude that the population mean is equal to 100. You cannot reject the null hypothesis. You conclude that the population mean is equal to 100. HT_4337: X1 X2 98.83 101.49 99.12 101.20 100.29 108.60 104.35 108.52 99.86 98.04 99.85 104.61 100.54 102.83 98.58 92.59 102.45 98.88 98.85 106.84 98.31 100.43 108.35 93.41 99.85 97.14 96.08 97.85 102.16 100.68 99.67 103.87 101.55 102.16 95.60 107.93 102.23 99.43 96.54 103.00 99.52 109.33 93.08 105.23 102.38 96.85 96.76 98.83 99.20 102.46 97.38 101.29 93.57 100.07 99.40 104.86 101.71 101.02 104.12 105.26 100.18 100.61 103.50 101.57 101.07 100.15 97.07 96.16 97.77 102.14 99.35 93.08 100.95 104.60 104.25 97.53 95.81 98.98 98.53 105.70

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

Use the dataset HT_4337.xls. Using Excel, conduct a t-test (at the alpha = 0.05 significance level) on whether the mean of X1 is equal to 100. What do you conclude from this sample data? Is the population mean equal to 100?

Group of answer choices

You cannot reject the null hypothesis. You conclude that the population mean is not equal to 100.

You reject the null hypothesis. You conclude that the population mean is not equal to 100.

You reject the null hypothesis. You conclude that the population mean is equal to 100.

You cannot reject the null hypothesis. You conclude that the population mean is equal to 100.

HT_4337:

X1         X2
98.83   101.49
99.12    101.20
100.29   108.60
104.35   108.52
99.86     98.04
99.85    104.61
100.54   102.83
98.58     92.59
102.45    98.88
98.85     106.84
98.31     100.43
108.35   93.41
99.85     97.14
96.08     97.85
102.16   100.68
99.67     103.87
101.55   102.16
95.60    107.93
102.23   99.43
96.54    103.00
99.52    109.33
93.08     105.23
102.38    96.85
96.76     98.83
99.20    102.46
97.38     101.29
93.57     100.07
99.40     104.86
101.71    101.02
104.12    105.26
100.18    100.61
103.50    101.57
101.07    100.15
97.07      96.16
97.77     102.14
99.35      93.08
100.95   104.60
104.25
97.53
95.81
98.98
98.53
105.70

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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