1. Outliers are usually eliminated from data analysis. However, there are cases where you would not want to eliminate outliers. Discuss why you would want to keep outliers in your analysis. Give 2 examples from the industry in which you work. e.g. Fraudulent transactions detection in banking. 2. If for a certain continuous variable {measure} the 25th percentile value is HUD and the ?5\"' percentile value is 13m, what values could be considered outliers based on the rule of thumb 1.5 * l? 3. As part of a data analytics project, Wollongong city council wants utilities consumption data analysed at postcode level. They are interested in calculating the ratio between per capita water use and per ca pita electricity use. If the structure of the data table they use is given below, write a formula to calculate this new measure. In your formula, just use the variabler'column names. Postcode total_water_usage total_electricity_usage population [mL] [kwh] 150i] ll 4. If your company wants you to visualise average age of customers {mea sure i, their monthly income [measure], distance from the nearest retail store to home [measure] and the industry sector in which they work [category]. what kind of chart would you use. Explain and sketch. 5. Given the below table. come up with 4 interesting questions [hypothesesl you could