摘要：import numpy as np import statsmodels.formula.api as smf import pylab as plt x = np.arange(17, 30, 2); a = np.loadtxt('data10_3.txt') plt.rc('text', u 阅读全文

摘要：import numpy as np import statsmodels.api as sm import pylab as plt a = np.loadtxt('data10_2.txt') plt.rc('text', usetex=True); plt.rc('font', size=16 阅读全文

摘要：import numpy as np import statsmodels.api as sm import pylab as plt def check(d): x0 = d[0]; y0 = d[1]; d ={'x':x0, 'y':y0} re = sm.formula.ols('y~x', 阅读全文

摘要：import pandas as pd from statsmodels.formula.api import ols from statsmodels.stats.anova import anova_lm import openpyxl column_names = ['城市1', '城市2', 阅读全文

摘要：import pandas as pd import statsmodels.api as sm from statsmodels.formula.api import ols from statsmodels.stats.anova import anova_lm file_path = '9.4 阅读全文

摘要：import numpy as np import matplotlib.pyplot as plt from scipy.stats import norm plt.rcParams['text.usetex'] = False mu, sigma = 0, 1 x = np.linspace(m 阅读全文

摘要：程序文件ex9_4.py from scipy.stats import expon print(expon.stats(scale=3, moments='mvsk')) print("学号后两位：04") 阅读全文

摘要：程序文件ex9_3.py from scipy.stats import norm from scipy.optimize import fsolve c1 = norm.ppf(0.25, 3, 2) #求0.25分位数 fc = lambda c: 1-norm.cdf(c, 3, 2)-3*n 阅读全文

摘要：import numpy as np # 导入 numpy 库 import matplotlib.pyplot as plt # 导入 matplotlib.pyplot 库 from scipy.stats import binom # 从 scipy.stats 导入 binom 模块 设置试 阅读全文

摘要：程序文件ex9_1.py from scipy.stats import expon, gamma import pylab as plt x = plt.linspace(0, 3, 100) L = [1/3, 1, 2] s1 = ['*-', '.-', 'o-'] s2 = ['\(\\t 阅读全文

摘要：import pandas as pd import matplotlib.pyplot as plt import seaborn as sns from scipy import stats file_path = '9.3.xlsx' data = pd.read_excel(file_pat 阅读全文

摘要：某车间生产滚珠，随机的抽出了50粒，测得他们的直径为（单位mm）15.0 15.8 15.2 15.1 15.9 14.7 14.8 15.5 15.6 15.3 15.1 15.3 15.0 15.6 15.7 14.8 14.5 14.2 14.9 14.9 15.2 15.0 15.3 15. 阅读全文

摘要：def calculate_monthly_payment(P, annual_interest_rate, n_years): monthly_interest_rate = annual_interest_rate / 12 / 100 total_months = n_years * 12 M 阅读全文

摘要：有四个年龄组的鱼。该鱼类在每年后4个月季节性集中产卵繁殖。按规定，捕捞作业只允许在前8个月进行，每年投入的捕捞能力固定不变。单位时间捕捞量鱼各年龄组鱼群条数的比例称为捕捞强度系。使用只能捕捞3、4龄鱼的13mm网眼的拉网，其两个捕捞强度系数比为0.42：1。各年龄组鱼的自然死亡率为0.8（1/年）， 阅读全文

摘要：程序文件ex8_8.py from scipy.integrate import odeint import numpy as np import pylab as plt yx = lambda y,x: [y[1], np.sqrt(1+y[1]**2)/5/(1-x)] x0 = np.ara 阅读全文

摘要：程序文件ex8_7.py from scipy.integrate import odeint import numpy as np import pylab as plt import sympy as sp dy = lambda y, x: -2y+2x2+2x #自变量在后面 xx = np 阅读全文

摘要：程序文件ex8_6.py import sympy as sp sp.var('t') sp.var('x1:4', cls=sp.Function) #定义3个符号函数 x = sp.Matrix([x1(t), x2(t), x3(t)]) #列向量 A = sp.Matrix([[3,-1,1 阅读全文

摘要：程序文件ex8_5.py import sympy as sp sp.var('t'); y=sp.Function('y') u=sp.exp(-t)sp.cos(t) eq=y(t).diff(t,4)+10y(t).diff(t,3)+35y(t).diff(t,2)+ 50y(t).diff 阅读全文

摘要：程序文件ex8_4.py import sympy as sp sp.var('x'); y=sp.Function('y') eq=y(x).diff(x,2)-2*y(x).diff(x)+y(x)-sp.exp(x) con={y(0): 1, y(x).diff(x).subs(x,0): 阅读全文

摘要：程序文件ex8_3.py import sympy as sp sp.var('x'); y=sp.Function('y') eq=y(x).diff(x)+2y(x)-2x**2-2*x s=sp.dsolve(eq, ics={y(0):1}) s=sp.simplify(s); print( 阅读全文