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What are some instances of trends and seasonal patterns in time series data?
Trends in time series data show long-term changes or patterns over time, such as increasing or decreasing values. Examples include population growth, stock market trends, or climate change....
Which technique is commonly used for handling outliers in data?
One commonly used technique for handling outliers in data is trimming or winsorizing. Trimming involves removing a certain percentage of extreme values from the upper and lower tails of the dataset,...
Which data set should I use to apply linear regression?
Choosing a dataset for linear regression depends on your research question and the availability of relevant variables. Datasets with continuous dependent variables and numeric independent variables...
What processes are involved in the statistical analysis of clinical trial data with SAS?
Statistical analysis of clinical trial data with SAS often consists of many phases. First, data cleaning and validation are performed to verify data accuracy. The data is then summarised using...
How can I discover outliers in time series data?
There are various approaches for identifying outliers in time series data. One typical strategy is to employ statistical approaches like the z-score or modified z-score method, in which data points...
Logistic Regression Definition
Logistic regression is a statistical approach used for binary classification problems in which the result variable is categorical and has two alternative outcomes, usually recorded as 0 and 1....
What causes skewness in data is due to outliers always?
Skewness in data happens when the value distribution is asymmetric, with one side having a larger tail than the other. Outliers can contribute to skewness, but they are not the only source. Skewness...
Best Model Choice for a non-linear Regression
There are various model options for nonlinear regression problems, with selection determined on data attributes and modelling aims. Polynomial regression extends linear regression by include...
Cluster Algorithm in Machine learning
Cluster methods in machine learning combine comparable data points based on specific attributes or qualities. K-means, hierarchical clustering, and DBSCAN are among the most often used methods....
Anova in SAS
In SAS (Statistical Analysis System), Analysis of Variance (ANOVA) is a statistical tool for examining mean differences across groups. It is useful in determining if there are statistically...
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