#创作灵感#

MATLAB基础知识官方课程学习笔记

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MATLAB Fundamentals>Common Data Analysis Techniques>Summary of Common Data Analysis Techniques>(2/2) Project - Analyze Vehicle Data

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任务名称：Fuel Economy Analysis

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任务1：

The variable mpg contains NaN values. Find the rows in mpg with NaN values, and remove those rows from all three data vectors: mpg, hp, and wt.

解答1：

nanIdx = ismissing(mpg)
mpg = mpg(~nanIdx);
hp = hp(~nanIdx);
wt = wt(~nanIdx);

结果1：

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背景：

Fuel economy in the U.S. is typically given in miles/gallon. In many countries, however, the standard units are liters/100km.

Given mpg, you can calculate economy in L/100km by dividing 235.214583 by mpg.

任务2：

Create a variable econ that contains the fuel economy in L/100km rather than miles/gallon.

Combine the data for weight, horsepower, and fuel economy in L/100km (in that order) into a 48-by-3 matrix called numdata.

解答2：

econ = 235.214583./mpg
numdata = [wt hp econ]

笔记：注意mpg是个向量，需要使用”./“。

结果2：

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任务3：

Create a matrix of the scatter plots of the variables in numdata (weight, horsepower, and fuel economy) in a single figure.

Calculate the corresponding correlation coefficients and store them as a matrix called cc.

解答3：

plotmatrix(numdata)
cc = corrcoef(numdata)

结果3：

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任务4：

Determine the best-fit line (i.e., a first degree polynomial fit) for fuel economy (in L/100km) as a function of vehicle weight.

Evaluate the fitted model at the weights in the data. Store the fitted values in a vector called econFit.

Note that you do not need to use centering and scaling for the fit.

解答4：

c = polyfit(wt,econ,1)
econFit = polyval(c,wt)

结果4：

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任务5：

Create a scatter plot of fuel economy against weight, and add the best-fit line as a red line.

解答5：

scatter(wt,econ)
hold on 
plot(wt,econFit,"r")
hold off

结果5：

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附加练习：

Try fitting a line to horsepower as a function of weight. Try plotting both scatter plots and fits together, using yyaxis to accommodate the different scales:
 

附加练习解答：

chp = polyfit(wt,hp,1)
hpFit = polyval(chp,wt)
yyaxis right
hold on
scatter(wt,hp)
plot(wt,hpFit)
hold off

附加练习结果：