Category : statistics

I have a data set : Google Sheet Data While performing a Two sample t test assuming unequal variances , the excel output is this : I am trying to replicate the same in python using : T_test = ttest_ind(df.dropna()[‘PRE’],rest.dropna()[‘POST’],equal_var=False, alternative="less) result = T_test[1] The p value from scipy is 0.004689 where as in excel ..

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I am trying to create a box plot with matplotlib library of python. The code is given below. fig, ax = plt.subplots(figsize=(8, 6)) bp = ax.boxplot([corr_df[‘bi’], corr_df[‘ndsi’], corr_df[‘dbsi’], corr_df[‘mbi’]], patch_artist = True, notch =’True’, vert = 1) ax.set_title("Spearman’s correlation coefficient for Soil indices", fontsize=14) ax.set_xlabel("Indices", fontsize=14) ax.set_ylabel("Spearman’s correlation coefficient", fontsize=14) colors = [‘#088A08’, ‘#FFFF00′,’#01DFD7’, ‘#FF00FF’, ..

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I have a dataset where every data sample consists of 10-20 2D coordinates points. The data is mostly clean but occasionally there are falsely annotated points. For illustration the cleany annotated data would look like these: either clustered in a small area or spread across a larger area. The outliers I’m trying to filter out ..

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How to calculate the gradient (or derivative) of y = f(x) of y w.r.t x where y represents the order statistics divided by median of x? For instance x is [3, 2, 1, 5, 4] when y=f(x) would be [1/3, 2/3, 1, 4/3, 5/3]. How can I calculate the derivative of y with respect to ..

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