I don't need a code for these questions. I just need them answered Nine steel specimens were submerged in seawater at various temperatures, and the corrosion rates were measured. The results are presented in the following table: Temperature (OC) Corrosion (mm/yr.) 26.6 1.58 26 1.45 27.4 1.13 21.7 0.96 14.9 0.99 11.3 1.05 15 0.82 8.7 0.68 8.2 0.59 a. Construct a scatterplot of corrosion (y) vs. temperature (x). Verify that a linear model is appropriate. b. What is the least-square line (trendline/regression line) for predicting corrosion from temperature? c. Two steel specimens whose temperatures differ by 10OC are submerged in seawater. By how much would you predict their corrosion rates differ? d. Predict the corrosion rate for steel submerged in seawater at a temperature of 20OC. e. Construct a table with predicted values from the original dataset. f. Compute the residuals. Which point has the residual with the largest magnitude? g. What is the correlation between temperature and corrosion rate? What is the regression value? What can be said about variability? h. Construct a residual plot. What conclusions can be drawn from this plot.
I don't need a code for these questions. I just need them answered
Nine steel specimens were submerged in seawater at various temperatures, and the corrosion
rates were measured. The results are presented in the following table:
Temperature
(OC)
Corrosion
(mm/yr.)
26.6 1.58
26 1.45
27.4 1.13
21.7 0.96
14.9 0.99
11.3 1.05
15 0.82
8.7 0.68
8.2 0.59
a. Construct a scatterplot of corrosion (y) vs. temperature (x). Verify that a linear model is
appropriate.
b. What is the least-square line (trendline/regression line) for predicting corrosion from
temperature?
c. Two steel specimens whose temperatures differ by 10OC are submerged in seawater. By how
much would you predict their corrosion rates differ?
d. Predict the corrosion rate for steel submerged in seawater at a temperature of 20OC.
e. Construct a table with predicted values from the original dataset.
f. Compute the residuals. Which point has the residual with the largest magnitude?
g. What is the correlation between temperature and corrosion rate? What is the regression value?
What can be said about variability?
h. Construct a residual plot. What conclusions can be drawn from this plot.
Introduction
DataSet:
A dataset is a collection of related data points that are organized and structured for easy use and analysis. In the context of computing, a dataset may refer to any type of digital information, such as a collection of images, a set of text documents, a table of numerical values, or any other type of structured or unstructured data.
Datasets are used in a wide range of applications, including scientific research, machine learning, data mining, and business intelligence. They can be used to identify patterns, relationships, and insights within the data, and to make informed decisions or predictions based on that information.
Datasets can be collected from various sources, such as surveys, experiments, observations, or from existing databases. They can also be created by scraping data from websites or other online sources. Once collected, the data is usually cleaned, processed, and transformed into a format that is suitable for analysis.
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