Data Management - Statistical AnaylsisPer the following graph, explain the reason for every statistic that is calculated. For example, You have a scatter plot of an hourly wages vs level of education, the trend is represented by a cubic curve with R^2=0.999. It can mean that the relationship of the level of education vs the hourly wages has a cubic trend as the cubic model suits well the set of data (R^2 is very close to 1). 700060005000400030002000100002019-12-012020-03-102020-06-182020-09-26Number of Cases by Episode Date2021-01-042021-04-14● Active ● Recovered ●Deceased2021-07-232021-10-31:2022-02-082022-05-192022-08-27 Graph 3:ActiveMean4.8698296836983Median0Mode0Range462Standard 36.870DeviationSampleVarianceQuartilesActive CasesRecoveredQ1068Q20187.5Q30511IQR for Active Cases = Q3 - Q1 = 0 -0 =0IQR for Recovered Cases = Q3 - Q1 = 511 - 68 = 443IQR for Deceased Cases = Q3 - Q1 =8-0=81492.6274RecoveredMeanMedianModeRangeStandardDeviationSampleVariance389.514598187.515864591.201866349945.31DeceasedMeanMedianModeRangeStandardDeviationSampleVarianceDeceased02285.173965920497.032436649.5153758

For Active, Mean=4.8698 Median=0 There is no mode in the data That is, the mean is greater than the…

Answered: Per the following graph, explain the…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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Data Management - Statistical Anaylsis

Per the following graph, explain the reason for every statistic that is calculated.

For example, You have a scatter plot of an hourly wages vs level of education, the trend is represented by a cubic curve with R^2=0.999. It can mean that the relationship of the level of education vs the hourly wages has a cubic trend as the cubic model suits well the set of data (R^2 is very close to 1).

7000
6000
5000
4000
3000
2000
1000
0
2019-12-01
2020-03-10
2020-06-18
2020-09-26
Number of Cases by Episode Date
2021-01-04
2021-04-14
● Active ● Recovered ●Deceased
2021-07-23
2021-10-31
:
2022-02-08
2022-05-19
2022-08-27

Graph 3:
Active
Mean
4.8698296836983
Median
0
Mode
0
Range
462
Standard 36.870
Deviation
Sample
Variance
Quartiles
Active Cases
Recovered
Q1
0
68
Q2
0
187.5
Q3
0
511
IQR for Active Cases = Q3 - Q1 = 0 -0 =0
IQR for Recovered Cases = Q3 - Q1 = 511 - 68 = 443
IQR for Deceased Cases = Q3 - Q1 =8-0=8
1492.6274
Recovered
Mean
Median
Mode
Range
Standard
Deviation
Sample
Variance
389.514598
187.5
1
5864
591.201866
349945.31
Deceased
Mean
Median
Mode
Range
Standard
Deviation
Sample
Variance
Deceased
0
2
28
5.1739659
2
0
49
7.0324366
49.515375
8

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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