CompTIA Data+ DA0-001 Reddit Questions

his is because median is a type of statistical measure that represents the typical value or central tendency of a data set, which means that it divides the data set into two equal halves, such that half of the values are above it and half are below it. Median can be used to provide a measure that represents the typical income of suburban families in the United States, especially when the data set has a lot of outliers, which means that it has values that are unusually high or low compared to the rest of the data set. Median can provide a measure that represents the typical income of suburban families in the United States, because it is not affected or skewed by the outliers, as it only depends on the middle value or the middle two values of the data set, regardless of how extreme or distant the outliers are. For example, median can provide a measure that represents the typical income of suburban families in the United States, by finding the income value that splits the data set into two equal groups of families, such that 50% of the families have higher incomes and 50% have lower incomes. The other statistical measures are not the best measures to represent the typical income of suburban families in the United States. Here is why:

Mean is a type of statistical measure that represents the average value or central tendency of a data set, which means that it is the sum of all the values divided by the number of values. Mean is not a good measure to represent the typical income of suburban families in the United States, especially when the data set has a lot of outliers, because it is affected or skewed by the outliers, as it takes into account all the values in the data set, regardless of how extreme or distant they are. For example, mean can provide a measure that does not represent the typical income of suburban families in the United States, by finding the income value that is influenced by a few very high or very low incomes, which could make it higher or lower than most of the incomes in the data set.

Mode is a type of statistical measure that represents the most frequent value or mode of a data set, which means that it is the value that occurs most often in the data set. Mode is not a good measure to represent the typical income of suburban families in the United States, especially when the data set has a lot of outliers, because it is not representative or indicative of the central tendency or distribution of the data set, as it only depends on the count or occurrence of a single value or a few values in the data set, regardless of how common or rare they are. For example, mode can provide a measure that does not represent the typical income of suburban families in the United States, by finding the income value that is repeated more often than others, which could be an outlier or an anomaly in the data set.

Standard deviation is a type of statistical measure that represents the amount of dispersion or variation of a data set, which means that it quantifies how much the values in a data set vary or deviate from the mean or average of the data set. Standard deviation is not a measure that represents the typical income of suburban families in the United States, but rather a measure that describes the spread or distribution of their incomes, as well as identifies any outliers or extreme values in their incomes. For example, standard deviation can provide a measure that describes how diverse or homogeneous their incomes are, as well as how far their incomes are from their average income.

The correct answer is D. $702,500.

To find the price of the Rose unit, we need to use the average cost per square foot of the original floor plans. The average cost per square foot is calculated by dividing the price by the square footage of each unit type. Using the data from the table, we can do the following:

Jasmine: $345,000 / 1,000 = $345 per square foot

Orchid: $525,000 / 2,000 = $262.5 per square foot

Azalea: $375,000 / 1,500 = $250 per square foot

Tulip: $450,000 / 1,800 = $250 per square foot

The average cost per square foot of the original floor plans is the mean of these four values, which is ($345 + $262.5 + $250 + $250) / 4 = $276.875 per square foot.

To find the price of the Rose unit, we need to multiply the average cost per square foot by the square footage of the Rose unit. The Rose unit has a square footage of 2,535, according to the table. Therefore, the price of the Rose unit is $276.875 x 2,535 = $702,421.875.

Rounding to the nearest whole number, we get $702,500 as the price of the Rose unit.

Getting stakeholder approval is the next step the analyst should take in the dashboard creation process, after confirming the data sources and creating a wireframe. Stakeholder approval means getting feedback and validation from the intended users or clients of the dashboard, to ensure that it meets their expectations and requirements. This step helps to avoid rework and ensure customer satisfaction. References: CompTIA Data+ Certification Exam Objectives, page 14