And the standard deviation is 1 Thus , after standardization , the values are within the same range , the mean is 0 and the standard deviation is 1. Example fromsklearn.preprocessingimportStandardScalerimportnumpyasnp# Create a sample data matrixX=np.array([[85,72,80],[64,35,26],[67,48...
stddev- the standard deviation of all entries in the sample skewness- the statistical skewness of all entries in the sample kurtosis- the statistical kurtosis of all entries in the sample num_zeros- the number of entries in this sample that have the value 0 ...
Learn about the standard deviation of return, its significance in finance, and how it can be used to measure investment risk.
Chapter 4, Data Transformation, is where you will take your first steps in data wrangling. We will see how to merge database-style DataFrames, merge on the index, concatenate along an axis, combine data with overlaps, reshape with hierarchical indexing, and pivot from long to wide format. ...
What is a regression line? A regression line is a straight line used in linear regression to indicate a linear relationship between one independent variable (on the x-axis) and one dependent variable (on the y-axis). Regression lines may be used to predict the value of Y for a given val...
Python: Provides powerful libraries such as Pandas, NumPy, and Matplotlib for in-depth analysis. R: Proficient in advanced statistical techniques and efficient modeling. Power BI:Simplifies the creation of interactive dashboards and detailed reports. ...
In a boxplot graph, the box represents the data’s interquartile range (IQR), which is the 50 percent of data points above the first quartile and below the third quartile. Each whisker (line) on the side of a boxplot represents the top and bottom 25 percent of data points, where the...
Since winsorization is a statistical technique applied to a measure, it can be extended to other usual statistical measures. Let’s explore some other measures which winsorization can be applied to: Winsorized sample deviation: The winsorized version of the standard deviation measures the dispersio...
removes the mean and scales each feature/variable to unit variance. This operation is performed feature-wise in an independent way. StandardScaler can be influenced by outliers (if they exist in the dataset) since it involves the estimation of the empirical mean and standard deviation of each ...
In most regression problems, mean squared error is used to determine the model's performance. 3. What is Root Mean Squared Error or RMSE RMSE is the standard deviation of the errors which occur when a prediction is made on a dataset. This is the same as MSE (Mean Squared ...