of time as the soil dries out. The researcher hypothesized a decreasing trend, possibly linear, in time. Letting y = soil moisture and x = sample time, the estimated regression line is ŷ = 2.46 – 0.012r Suppose that you are the reviewer of this paper. Comment about the statistical analysis. The data is provided by the researcher (soil.csv) because the journal requires the attachment of data. So, you can use this data to clarify the problems if any.

of time as the soil dries out. The researcher hypothesized a decreasing trend, possibly linear, in time. Letting y = soil moisture and x = sample time, the estimated regression line is ŷ = 2.46 – 0.012r Suppose that you are the reviewer of this paper. Comment about the statistical analysis. The data is provided by the researcher (soil.csv) because the journal requires the attachment of data. So, you can use this data to clarify the problems if any.

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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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

A long term crop rotation study was conducted in Eastern Arkansas to deter-
mine the impacts of common crop management techniques on the properties of
the soil under cultivation. One aspect of the study was to model soil moisture
patterns over a growing season for each treatment combination and to compare
trends across the various treatments. Daily soil moisture and soil temperature
readings were taken at 10 minute intervals by automatic data loggers. In this
example, soil moisture at six hour intervals over a ten day period that began at
8:00 AM on the first day of the period immediately following a rain event. The
objective was fit a model that describes the soil moisture trend as a function
of time as the soil dries out. The researcher hypothesized a decreasing trend,
possibly linear, in time. Letting y = soil moisture and x = sample time, the
estimated regression line is
ŷ = 2.46 – 0.012.x
Suppose that you are the reviewer of this paper. Comment about the statistical
analysis. The data is provided by the researcher (soil.csv) because the journal
requires the attachment of data. So, you can use this data to clarify the problems
if any.

day.of.year time.of.day sampling.time soil.temperature soil.water.content
174 8am
174.25
24
0.358
174 2pm
174 8pm
174.5
29.85
0.352
174.75
31.4
0.346
175 2am
175
27.44
0.338
175 8am
175.25
25.05
0.331
175 2pm
175.5
29.98
0.329
175 8pm
175.75
31.29
0.325
176 2am
176
27.8
0.318
176 8am
176.25
25.2
0.313
176 2pm
176.5
29.84
0.311
176 8pm
176.75
31.27
0.309
177 2am
177
27.46
0.303
177 8am
177.25
24.87
0.298
177 2pm
177.5
29.56
0.298
177 8pm
177.75
30.17
0.296
178 2am
178
26.5
0.291
178 8am
178.25
24.89
0.288
178 2pm
178.5
28.38
0.288
178 8pm
178.75
32.68
0.288
179 2am
179
27.53
0.283
179 8am
179.25
25.2
0.28
179 2pm
179.5
30.44
0.279
179 8pm
179.75
34.34
0.278
180 2am
180
28.92
0.275
180 8am
180.25
26.5
0.272
180 2pm
180.5
31.41
0.27
180 8pm
180.75
34.61
0.267
181 2am
181
29.61
0.265
181 8am
181.25
27.09
0.262
181 2pm
181.5
31.79
0.26
181 8pm
181.75
35
0.256
182 2am
182
30.23
0.254

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