Based on this output, what are the sample mean income and standard error of the mean income – ROUNDED TO THE NEAREST DOLLAR? Suppose you somehow found out that the mean income for the population was in fact $78,000. Based only on the confidence interval that you estimated, to what extent would you find that a reasonable number? Why? Case Processing SummaryCasesValidMissingTotalPercentPercentNPercentIncome1020100.0%0.0%1020100.0%DescriptivesStatisticStd. ErrorIncomeMean79189.871663.48999% Confidence IntervalLower Bound74896.97for MeanUpper Bound83482.785% Trimmed Mean76294.04Median67466.35Variance2822540217Std. Deviation53127.584Minimum36Maximum212304Range212268Interquartile Range72301Skewness.798.077Kurtosis-.271.153

By the given output, we can observe that Mean=$79189.87 Standard error of sample mean=$1663.489…

Answered: Based on this output, what are the…

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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Based on this output, what are the sample mean income and standard error of the mean income – ROUNDED TO THE NEAREST DOLLAR?

Suppose you somehow found out that the mean income for the population was in fact $78,000. Based only on the confidence interval that you estimated, to what extent would you find that a reasonable number? Why?

Case Processing Summary
Cases
Valid
Missing
Total
Percent
Percent
N
Percent
Income
1020
100.0%
0.0%
1020
100.0%
Descriptives
Statistic
Std. Error
Income
Mean
79189.87
1663.489
99% Confidence Interval
Lower Bound
74896.97
for Mean
Upper Bound
83482.78
5% Trimmed Mean
76294.04
Median
67466.35
Variance
2822540217
Std. Deviation
53127.584
Minimum
36
Maximum
212304
Range
212268
Interquartile Range
72301
Skewness
.798
.077
Kurtosis
-.271
.153

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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