Business Data Analysis — final assessment

Skills covered

Identify confounding variables · Classify variable types · Identify the unit of observation · Detect and correct nonresponse bias · Explain random assignment and control groups · Separate statistical from practical significance · Choose a measure of centre · Calculate the interquartile range · Match summaries to the data · Flag outliers with the 1.5 × IQR rule · Calculate and interpret the coefficient of variation · Calculate a weighted mean · Average growth rates with the geometric mean · Compare values on different scales · Write a summary for a report · Choose a chart for the question and variable types · Recognise misleading charts · Read ECDF plots · Judge normality from a Q-Q plot · Read correlation matrices and heatmaps · Build and read box plots · Write chart titles and summaries that state the finding · Run a two-sample t-test · Interpret and communicate a test result · Run a paired t-test · Compare two proportions · Test a single proportion · Plan power and sample size · Control error rates across many tests · Report and judge effect sizes · Reason about Type I and Type II errors · Compute and interpret a p-value · Choose an appropriate test · Identify confounding, reverse causation and coincidence · Use and interpret log transformations · Code and interpret categorical predictors · Diagnose multicollinearity with VIFs · Fit and interpret multiple regression · Diagnose a model from residual plots · Interpret slopes and intercepts in context · Test a correlation and give a confidence interval · Distinguish confidence and prediction intervals · Interpret R² and the residual standard error · Interpret odds and odds ratios · Compare models with adjusted R² and F tests · Recognise extrapolation · Recognise overfitting · Run a chi-square test of independence · Calculate expected counts under independence · Run and interpret the Kruskal–Wallis test · Run and interpret the Mann–Whitney U test · Choose a test from the study design and data · Fit and read a two-way ANOVA · Interpret interactions and interaction plots · Check the assumptions of ANOVA · Explain why many tests inflate the error rate · Run and interpret post-hoc comparisons · Report η² and ω² for ANOVA · Check the conditions for a chi-square test · Find duplicate records · Detect impossible values and unit errors · Measure the effect of cleaning on results · Find and count missing values · Decide how to handle missing values · Write and document cleaning rules · Group and aggregate data · Transform variables · Select a method that fits the question and data · Write an analysis report · Record reproducible analysis steps