Making Decisions About Appropriate Statistical Analyses to Conduct

• basic frequencies
• charts and graphs [bar graphs, pie charts, histograms, line graphs, time series charts]
• measures of central tendency [mean, median, mode]
• measures of dispersion [range, IQR, variance / standard deviation, z-scores]
• contingency tables [bivariate or multivariate]
• confidence interval for the mean
• confidence interval for the proportion
• one sample T-Test
• independent samples t-test
• ANOVA (Analysis of Variance)
• chi-square
• measures of association (lambda / Cramer's V, Gamma / Kendall's tau-b)
• correlation (Pearson' r)
• basic linear regression (bivariate/multiple)

Some researchers have found that less-affluent neighborhoods have fewer places to buy healthy types of food. You wish to test this hypothesis in the southwest region of the United States and see if it is true on average. Therefore, you draw a random and representative sample of 500 neighborhoods throughout the Southwestern states and classify them based on their income level (lower-income, middle-income and upper-income). For each neighborhood in your sample, you also measure the number of places available where residents can buy healthy foods. You conduct your statistical analysis and hope to present your findings to stakeholders and community groups.

Out of the decisions listed above, which would you use for your statistical analyses?