Please help me explain how to do these questions:

In a data set with 23 variables, if 11% of the values, randomly spread across observations, are missing (blank), what is the probable percent of complete and usable observations? Multiple Choice o 7.70% 6.85% 11% 000 Henry wants to analyze Income, but the sheer number of categories In the data's current form wIll make a clear analysis less meaningful. In Excel with Analytic Solver, how wIll Henry determine the frequency of each category to transform his data? Multiple Choice O Income variable is selected and Analytic Solver produces a new category for nan-use variables. Inspect the frequency of Income category: >tablclmyData$Income). . Apply a limit to the number of categories from the drop-down to a reasonable number. O Income variable is selected and Analytic solver produces frequency levels for each income category from most to least frequent. Using the omission strategy, what value would be placed in the missing observation in X1? X1 X2 79 22 85 91 32 41 88 28 Multiple Choice 0 No value because excluded 69 86 84 0.0