# Explain which measure of spread would best describe the payroll:the range,the IQR, or the standard deviation.

Question
Explain which measure of spread would best describe the payroll:the range,the IQR, or the standard deviation.

2020-10-22
Inter quartile range:
In contrast to the range, which measures only differences between the extremes, the inter quartile range (also called mid spread) is the difference between the third quartile and the first quartile. Thus, it measures the variation in the middle 50 percent of the data and unlike the range it is not affected by extreme values. $$IQR = Q_{3} - Q_{1}$$.
Here, the range and the standard deviation affects by the two higher salaries whereas the interquartile range is not affected by the higher salaries.
Thus, the IQR is the measure of spread that best describe the payroll distribution.

### Relevant Questions

Explain which measure of center best describes a typical wage at this company:the mean or the median.
Explain the effect of correcting the error has on the IQR and the standard deviation.
The professor calculated the IQR and the standard deviation of the test scores in question 6 before realizing her mistake that is she entered the top score as 46 but it was actually 56.
To Explain:the expected the mean, median,standard deviation and IQR to change.
A meteorologist preparing a talk about global warming compiled a list of weekly low temperatures (in degree s Fahrenheit) he observed at his southern Florida home last year. The coldest temperature for any week was 36°F, but he inadvertently recorded the Celsius value of 2°. Assuming that he correctly listed all the other temperatures, explain how this error will affect these summary statistics:
a) measures of center: mean and median. b) measures of spread: range, IQR, and standard deviation.
Find the range and IQR of the data.
Which statement best characterizes the definitions of categorical and quantitative data?
Quantitative data consist of numbers, whereas categorical data consist of names and labels that are not numeric.
Quantitative data consist of numbers representing measurements or counts, whereas categorical data consist of names or labels.
Quantitative data consist of values that can be arranged in order, whereas categorical data consist of values that cannot be arranged in order.
Quantitative data have an uncountable number of possible values, whereas categorical data have a countable number of possible values.
Describe the spread in running times based on quartiles.
The data represents the average drive (in yards) for 186 professional golfers on the men’s PGA tour in 2011. The first quartile is 285.2 yards and third quartile is 297.5 yards.
Forecasting
Forecasting is important relative to capacity requirements planning.
What are some of the merits of using judgment methods (i.e., qualitative data) in contrast to quantitative forecasting methods.
Which methods are considered to be superior or more accurate, and in what forecast situations would require judgment methods?
In what situations would require a quantitative approach to forecasting?
True or False
1.The goal of descriptive statistics is to simplify, summarize, and organize data.
2.A summary value, usually numerical, that describes a sample is called a parameter.
3.A researcher records the average age for a group of 25 preschool children selected to participate in a research study. The average age is an example of a statistic.
4.The median is the most commonly used measure of central tendency.
5.The mode is the best way to measure central tendency for data from a nominal scale of measurement.
6.A distribution of scores and a mean of 55 and a standard deviation of 4. The variance for this distribution is 16.
7.In a distribution with a mean of M = 36 and a standard deviation of SD = 8, a score of 40 would be considered an extreme value.
8.In a distribution with a mean of M = 76 and a standard deviation of SD = 7, a score of 91 would be considered an extreme value.
9.A negative correlation means that as the X values decrease, the Y values also tend to decrease.
10.The goal of a hypothesis test is to demonstrate that the patterns observed in the sample data represent real patterns in the population and are not simply due to chance or sampling error.