Quantitative Analysis : Market Trends And Developments And Impact On The Business

1. For the following scores, find the mean, median, and the mode. Which would be the most appropriate measure for this data set?

This is a histogram were the tail goes to the right, it means the average is larger than the median.

Standard Deviation of Mean= 0.4762Standard Deviation of Median= 0.7539The standard deviation of the Mean is smaller, which means all of the data points will tend to be very close to the Mean. The Median with a larger Standard Deviation will tend to have data points spread out over a large range of values. Since the Mean has the smaller value of the Standard Deviations, it has the least variability.

Standard Deviation for the mean column is 0.476Standard Deviation for the median column is 0.754Standard deviation for the mean column has least variability

b. Ordinal: This is a measurement that represent the order of a particular stat. A good example of this would the placement in a contest, 1st, 2nd, and 3rd.

5. When is it more appropriate to use the median as a measure of center rather than the mean? Why?

Mean would be the most appropriate measure of central tendency to describe this data. This is because the mean is the average of all scores in the data set. If Dr. Williams were to graph the data into a bell shaped distribution, then the mean would be in the center where most of the scores are located. The mean is calculated using all information of the data set, and is the best score to use if you want to predict an individual score.

1. For the following scores, find the mean, median, and the mode. Which would be the most appropriate measure for this data set?

The last variable chose was number of prior drug convictions. The mean was .33 the median was 0 and the mode was 0. The mode is the most appropriate measure for this set of data because 957 people have had 0 prior drug convictions out of 1160. The next closest choice was 1 prior conviction with

Based on the given sample of student test scores of 50, 60, 74, 83, 83, 90, 90, 92, and 95 after rearranging them from least to greatest. As the mean is based on the average of sum, the average of this sample is 79.67 or 80. The mode refers to numbers that appear the most in a sequence and in this case 83 and 90 both appear twice. Range calculates the difference between the largest and smallest number, which are 95 and 50 which have a difference of 45. The variance is the difference between the sum of squares divided by the sample size, which is the number in the sample minus one (Hansen & Myers, 2012), meaning it takes each number of the set and subtracts

Median: 3, 5, 11, 12, 13, 15, 19, 35, 42, 65 = 13 + 15 = 28/2 = 14

“A measure of central tendency is a single value that attempts to describe a set of data by identifying the central position within that set of data (Laerd Statistics, 2013).” In terms of statistical data, the measurements could be mean, median, and mode. “The mean is equal to the sum of all the values in the data set divided by the number of values in the data set, the median is the middle score for a set of data that has been arranged in order of magnitude, and the mode is the most frequent score in our data set (Laerd Statistics, 2013).” BIMS can benefit from this type of statistical data because the company can get a good picture of the satisfaction

Based on the chart, the mean was calculated by adding up the sum of the list and divide 18, which the number of the total listed prices. The mean is 135,000, which mean the average of the listed price. Secondly, the median was calculated by listing the number in numerical order from lowest to highest and located the number in the middle 126,000. The median represents the middle number of the listed price. After calculating the median I located the minimum and maximum based the lowest and highest data, which are 48,000 and 338,000. These represent the range of the listed price. Lastly, I used the formula to get the

In this case, the business goes with the mean data analysis; the customers coming in the hotel will be within the range of 20kms. If they go with median data analysis, range will only be with in 20 and 25kms. And if the go with the mode data analysis, the range could be anything from 5 to 40kms

From that we can identify the typical costumer by calculate the mean of these two classes