Data Science: Expert Relationships In Data With Excel

Forecast Mars passenger volunteers using the attached data, applying data-driven methods to project future volunteer numbers amid terraforming and human adaptation.

Learn to measure the strength and direction of a linear relationship with the correlation coefficient r, from -1 to 1, where zero means no linear association.

Analyze a Mars data file (2030 to 2043) tracking passengers, net monthly income, inflation, ticket price, living space, personal space on board, health check cost, training duration, and Mars income.

Visualize data with a scatter plot in Excel to explore correlation, swap axis data, add axis titles, and spot outliers before computing the correlation coefficient.

Learn to compute correlation coefficients in Excel, from individual pairs to a correlation matrix, using passengers and average net monthly income to illustrate near -0.99.

Enable the analysis toolpak in Excel to access data analysis tools and perform advanced analyses, unlocking specialized options essential for data science with Excel.

Explore how to compute a correlation matrix in Excel using the Data Analysis Toolpak to assess relationships among multiple variables, including interpreting diagonal ones and notable coefficients.

Inspect the correlation matrix to scan data for variables linked to passenger numbers, noting strong negative ties to average net monthly income and positive ties to inflation and ticket price.

Explore how correlation captures linear relationships, not non-linear ones, so a low value may miss a real link. Detect how outliers distort the correlation coefficient and distinguish association from causality.

Respect outliers in data and examine their effect on correlation with a pool temperature and visitors example. Decide whether to remove or keep outliers based on context and domain.

Explore correlations by analyzing how a fictional Abc123 stock price relates to short-term rates, long-term rates, the S&P 500, unemployment, and crude oil prices in a simplified Excel data exercise.

Learn to build a correlation matrix with the Analysis Toolpak, select data with labels, and interpret strong correlations, such as between crude oil price and ABC 123 stock.

Explore how data delays affect correlations, and learn to apply time lags to uncover relationships between unemployment rate and discount-store revenue, using Excel.

Explore time lag analysis between promotional expenses and sales by calculating correlation coefficients across zero to three-week lags, using Excel to identify which lag best explains sales.

Explains how to test time lags in Excel by shifting promotional expenses to align with future sales, calculating correlations to identify lag two as the strongest relation.