、分别使用分段线性插值和样条插值预测 P196 例9.4 中的人口数。课本（第三 版）P202，习题14 数据：← data=[5.3,7.2,9.6,12.9,17.1,23.2,31.4.4 38.6,50.2,62.9,76.0,92.0,106.5,123.2,...4 131.7,150.7,179.3,204.0,226.5,251.4,275.0,308.71用MATLAB代码

分段线性插值代码：

% 数据
data=[5.3,7.2,9.6,12.9,17.1,23.2,31.4,38.6,50.2,62.9,76.0,92.0,106.5,123.2,131.7,150.7,179.3,204.0,226.5,251.4,275.0,308.7];

% 插值点
x = 1900:10:2020;

% 分段线性插值
y = interp1(1900:10:2020, data, x, 'linear');

% 绘图
plot(1900:10:2020, data, 'o', x, y, '-')
xlabel('Year')
ylabel('Population (million)')
title('Linear Interpolation')

样条插值代码：

% 数据
data=[5.3,7.2,9.6,12.9,17.1,23.2,31.4,38.6,50.2,62.9,76.0,92.0,106.5,123.2,131.7,150.7,179.3,204.0,226.5,251.4,275.0,308.7];

% 插值点
x = 1900:10:2020;

% 样条插值
pp = spline(1900:10:2020, data);
y = ppval(pp, x);

% 绘图
plot(1900:10:2020, data, 'o', x, y, '-')
xlabel('Year')
ylabel('Population (million)')
title('Spline Interpolation')

运行以上代码，即可得到分段线性插值和样条插值的预测结果，并绘制出插值曲线图。