Dmt Analysis

2. Based on the scale of measurement for each variable listed below, which measure of central tendency is most appropriate for describing the data?

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.

In our second assumption, instead of using the cost of goods per cases in 1986, we try to use the percentage it counts in the total expenses which is 50.4% and to find the sales needed to break-even. The detail of the calculation is shown in the answer for questions d. The result is that 95,635, a little bit higher than the estimated sales of 90,000.

Although the financial goal is to create profit, we need to calculate the breakeven point to get started.

At breakeven, Q=6,658 paying customers who will be in attendance with an additional .25 x 6,658 = 1,665 comp customers.

Standard deviation is important in comparing two different sets of data that has the same mean score. One standard deviation may be small (1.85), where the other standard deviation score could be quite large (10)(Rumsey,

In order to be able to distribute the values within this lab we will be using Histograms. Although this is similar to a bar graph histograms are very different. Where in a bar graph we make our bars in any given order a histograms purpose is understand the frequency

Conclusion: The drawn hypothesis is accepted, or in other words supported by the collected data to a certain extent. Both the raw data tables as well as the graphs show accuracy to a certain extent which goes to show that there was error, however minimal. The hypothesis stated the the more hypertonic the sucrose solution, the less increase in potato mass there will be. It even suggests that mass might increase.

• Airline’s profitability hinged on the fraction of its flown seats occupied by passengers- load factor

By computing number of cups of coffee students drink per week, out of 22 students 16 students are not consuming coffee so median and mode is 0 while the mean is 4.09 mainly because two students are consuming 28 times in a week. The standard deviation of the data is 8.60.

70% of seats are sold at the lowest two fares.30% of seats are charged at higher fares. The last 6% are sold at the highest fare

Choice (a) would not fit since stem plots are best used to display fairly small data sets and to see the distribution’s shape, and the appropriate choice, the boxplot, is also included as inappropriate when in actuality this is not true. Choice (c) is wrong since a bar graph and a pie chart are both used to compare categorical data, which is not being compared in this question. Although in choice (d) it is correct that a dot plot would be inappropriate since there aren’t any observed frequencies with the same scores, using a histogram would be inappropriate instead of appropriate since, it was already proven that using this type of graph is not the best when comparing a large data set as this one. Choice (e) is obviously wrong, since it was proven above that a boxplot is the most appropriate way to display the data, which disagrees with the statement that none of the above are correct.

This would account for 99.7% of the area under the curve. According to this theory, virtually all flights would have between 122 – 182 passengers.

Break-even point in total sales dollars =(Fixed expenses)/(CM ratios) = (400,000)/(0.5466) = 732,000 $ (Rounded)

As shown on the income statement the profit margin has been negative in the airline industry since 2000. However, in 2006 U.S. airlines generated an operating margin of 4.6 percent on operating profits. After factoring in $4.1 billion in interest expense, $653 million in income taxes and $301 million in miscellaneous non-operating income, the industry posted net earnings of $3.0 billion and net profit margin of only 1.9 percent. This was well below the average for U.S. corporations. In 2006 things started changing for the airline industry. In 2006 passenger airlines utilize nearly four fifths of the seating capacity. Also, rising passenger yield and aggressive cost control drove the average break-even load factor down