Using the `Explore` command in SPSS, the following statistics were computed to analyze income levels (`rincdol`) for both genders (`sex`): Results Table Statistic Males Females Mean [Insert Value] [Insert Value] Median [Insert Value] [Insert Value] Q1 (25th Percentile) [Insert Value] [Insert Value] Q3 (75th Percentile) [Insert Value] [Insert Value] Range [Insert Value] [Insert Value] Variance [Insert Value] [Insert Value] Standard Deviation [Insert Value] [Insert Value] Skewness [Insert Value] [Insert Value] Kurtosis [Insert Value] [Insert Value] Step 3: Interpretation of Results Comparison of Central Tendencies: The mean and median values highlight the average and middle income levels for males and females. Noticeable differences here may indicate disparities in income distribution. Income Spread: Quartiles (Q1, Q3) provide insight into the income ranges for each gender, while the range identifies the gap between the highest and lowest incomes. Variation in Data: Variance and standard deviation assess how income levels vary around the mean. Larger values suggest greater dispersion. Shape of Distribution: Skewness reveals the asymmetry of the data for each group. Positive skewness indicates a longer right tail, while negative skewness suggests a longer left tail. Kurtosis examines the sharpness or flatness of the distribution. High kurtosis implies a sharper peak, while low kurtosis indicates a flatter distribution. Key Insights: Highlight any significant disparities or trends observed in the income levels based on the measures calculated. Use the obtained statistics to substantiate claims or hypotheses regarding income distribution by gender.