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Statistical Analysis - Data Management  For the following graph, answer the following: mean, median, mode for the central tendency; st. deviation, variance, range, IQR, Quartiles for a spread of data; Equation of LOBF/ COBF, r, R^2 for characteristics of a trend model and how well it suits a set of data; cause-and-effect relations from scatter plots. Include the equation for the line/curve of best fit. You can analyze different models: linear, quadratic, exponential, polynomial, etc. 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).

Statistical Analysis - Data Management  For the following graph, answer the following: mean, median, mode for the central tendency; st. deviation, variance, range, IQR, Quartiles for a spread of data; Equation of LOBF/ COBF, r, R^2 for characteristics of a trend model and how well it suits a set of data; cause-and-effect relations from scatter plots. Include the equation for the line/curve of best fit. You can analyze different models: linear, quadratic, exponential, polynomial, etc. 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).

MATLAB: An Introduction with Applications
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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Statistical Analysis - Data Management 

For the following graph, answer the following:

  • mean, median, mode for the central tendency; st. deviation, variance, range, IQR, Quartiles for a spread of data; Equation of LOBF/ COBF, r, R^2 for characteristics of a trend model and how well it suits a set of data; cause-and-effect relations from scatter plots.
  • Include the equation for the line/curve of best fit. You can analyze different models: linear, quadratic, exponential, polynomial, etc.

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).

1000 900 800 700 600 500 400 300 200 100 0 12 to 19 Male Hospitalizations 0 to 4 Number of Hospitalization by Gender 20 to 39 40 to 59 5 to 11 Female Hospitalizations Total Hospitalizations Count 60 to 79 All ages 80 Unknown Sex Hospitalizations
Transcribed Image Text:1000 900 800 700 600 500 400 300 200 100 0 12 to 19 Male Hospitalizations 0 to 4 Number of Hospitalization by Gender 20 to 39 40 to 59 5 to 11 Female Hospitalizations Total Hospitalizations Count 60 to 79 All ages 80 Unknown Sex Hospitalizations
Period recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases Age group 0 to 4 12 to 19 20 to 39 40 to 59 5 to 11 60 to 79 All ages 80 Female Male Hospitalization Hospitalizati Hospitalizatio S ons 23 20 3 3 23 26 47 48 5 2 172 150 183 183 456 432 Total Unknown Sex ns Count Hospitalizati ons 43 0 6 49 95 7 324 367 891 DOOOON C 0 0 0 0 2 1 3
Transcribed Image Text:Period recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases recent COVID-19 cases Age group 0 to 4 12 to 19 20 to 39 40 to 59 5 to 11 60 to 79 All ages 80 Female Male Hospitalization Hospitalizati Hospitalizatio S ons 23 20 3 3 23 26 47 48 5 2 172 150 183 183 456 432 Total Unknown Sex ns Count Hospitalizati ons 43 0 6 49 95 7 324 367 891 DOOOON C 0 0 0 0 2 1 3
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