Statistical Analysis - Data Management Per each graph, answer the following: Any relevant statistics to support your findings (mean, median, mode, standard deviation, etc.) Include the equation for the line/curve of best fit. You can analyze different models: linear, quadratic, exponential, polynomial, etc. Explain the r2 and r value (if needed) see your notes from the appropriate section. How these stats characterize relationships between variables? Sampling techniques involved in a data collection. Population? Bias and extraneous variables. Final statement (future trends, what you expect to happen)
Statistical Analysis - Data Management Per each graph, answer the following: Any relevant statistics to support your findings (mean, median, mode, standard deviation, etc.) Include the equation for the line/curve of best fit. You can analyze different models: linear, quadratic, exponential, polynomial, etc. Explain the r2 and r value (if needed) see your notes from the appropriate section. How these stats characterize relationships between variables? Sampling techniques involved in a data collection. Population? Bias and extraneous variables. Final statement (future trends, what you expect to happen)
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
Per each graph, answer the following:
- Any relevant statistics to support your findings (mean,
median ,mode , standard deviation, etc.) - Include the equation for the line/curve of best fit. You can analyze different models: linear, quadratic, exponential, polynomial, etc.
- Explain the r2 and r value (if needed) see your notes from the appropriate section. How these stats characterize relationships between variables?
- Sampling techniques involved in a data collection. Population?
- Bias and extraneous variables.
- Final statement (future trends, what you expect to happen)
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