Compare the means of each group (ASPD and no ASPD). What can you say about the narcissism scores of the ASPD group compared to the no ASPD group? DescriptivesStd. ErrorStatisticASPDMean23.30002.9964895% Confidence IntervalLower Bound16.5215for MeanUpper Bound30.07855% Trimmed Mean23.5556Median26.5000Variance89.789Std. Deviation9.47570Minimum8.00Maximum34.00Range26.00Interquartile Range17.25Skewness-.632.687Kurtosis-.9171.334 DescriptivesStatisticStd. Errorno_ASPDMean9.90001.3034195% Confidence IntervalLower Bound6.9515for MeanUpper Bound12.84855% Trimmed Mean9.7222Median9.0000Variance16.989Std. Deviation4.12176Minimum5.00Maximum18.00Range13.00Interquartile Range6.50Skewness.732.687Kurtosis-.0361.334

Given information: The output of descriptive statistics is given.

Answered: Compare the means of each group (ASPD…

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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Compare the means of each group (ASPD and no ASPD). What can you say about the narcissism scores of the ASPD group compared to the no ASPD group?

Descriptives
Std. Error
Statistic
ASPD
Mean
23.3000
2.99648
95% Confidence Interval
Lower Bound
16.5215
for Mean
Upper Bound
30.0785
5% Trimmed Mean
23.5556
Median
26.5000
Variance
89.789
Std. Deviation
9.47570
Minimum
8.00
Maximum
34.00
Range
26.00
Interquartile Range
17.25
Skewness
-.632
.687
Kurtosis
-.917
1.334

Descriptives
Statistic
Std. Error
no_ASPD
Mean
9.9000
1.30341
95% Confidence Interval
Lower Bound
6.9515
for Mean
Upper Bound
12.8485
5% Trimmed Mean
9.7222
Median
9.0000
Variance
16.989
Std. Deviation
4.12176
Minimum
5.00
Maximum
18.00
Range
13.00
Interquartile Range
6.50
Skewness
.732
.687
Kurtosis
-.036
1.334

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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