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Descriptive Statistics

Summary Statistics

  • To give a thorough picture of the distribution of data, important metrics like mean, median, mode, standard deviation and variance are calculated and interpreted for understanding.

Data Visualization

  • Using scatter plots, bar charts, pie charts, and histograms to create visual representations of data that can be used to spot trends, patterns, and outliers.

Trend Analysis

  • The process of analysing data over time to identify and make sense of cycles, patterns, and seasonal changes.
  • Analysis of data over time to detect and interpret patterns, cycles, and seasonal variations.

Inferential Statistics

Hypothesis Testing

Conducting tests like t-tests, chi-square tests, ANOVA, TOST and regression analysis (linear, stepwise, polynomial and logistic) to draw conclusions about population parameters based on sample data.

Confidence Intervals

Estimating population parameters with a range of values derived from sample statistics, providing an indication of the reliability of estimates.

Correlation

Correlation is a tool used to evaluate the correlations between variables. Granger causality tests are one method used to find possible causal relationships.

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