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). 60.050.040.030.020.010.00.0Covid-19 Patients in ICU (Per 1 Million)Among Unvaccinated PeopleAmong People Vaccinated with at Least 2 Doses Graph 8:Patients in ICU (Per 1 million)Mean28.2Median28.2Mode48.3, 8.1Range40.220.1Standard DeviationSample Variance808.02QuartilesPatients in ICU (Per 1 million)UnknownQ1Q228.2Q3UnknownIQR for Patients in ICU = Q3 – Q1 = Unknown - Unknown = Unknown

For patients in ICU Mean=28.2 Median=28.2 Mode: 48.3, 8.1 The average number of patients in ICU per…

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

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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).

60.0
50.0
40.0
30.0
20.0
10.0
0.0
Covid-19 Patients in ICU (Per 1 Million)
Among Unvaccinated People
Among People Vaccinated with at Least 2 Doses

Graph 8:
Patients in ICU (Per 1 million)
Mean
28.2
Median
28.2
Mode
48.3, 8.1
Range
40.2
20.1
Standard Deviation
Sample Variance
808.02
Quartiles
Patients in ICU (Per 1 million)
Unknown
Q1
Q2
28.2
Q3
Unknown
IQR for Patients in ICU = Q3 – Q1 = Unknown - Unknown = Unknown

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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