There are mathematical models used to analyze and interpret data through statistical methods. These models describe, analyze, and make predictions or inferences about the relationships or patterns observed in data. Statistical models can be applied in economics, finance, and marketing.
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- Linear regression models are used to establish a relationship between two continuous variables. The model determines the best-fit line that summarizes the relationship between the variables.
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- Logistic regression models are used to analyze the relationship between a categorical outcome variable and one or more predictor variables. The model estimates the probability of an event occurring based on the predictor variables.
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- Time series models are used to analyze time series data, where data is collected at regular intervals over time. The model is used to predict future values based on past trends and patterns in the data.
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- ANOVA (Analysis of Variance). ANOVA models are used to compare means between two or more groups. The model determines if there are any significant differences between the groups and, if so, which group or groups differ.
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- Clustering models are used to group similar data points together based on the similarity of their attributes. The model can be used to identify patterns or segments in the data.
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- Decision tree models are used to classify data into categories based on a series of decisions or criteria. The model is used to identify the most relevant predictors or factors in the decision-making process.