IE 151 Homework 2 Continue With Microsoft Excel You Are Goin

Ie 151 Homework 2continue With Microsoft Excelyou Are Going To Turn I

IE 151 Homework #2 Continue with Microsoft Excel You are going to turn in one Excel file with each of the problems on another spreadsheet within the file, unless stated otherwise. 1) We are looking at the difference in the average rain per month between New Mexico and Arizona. We think that the amount of rain over the course of a year should be similar to each other, specifically around Las Cruces (for New Mexico) and Tucson (for Arizona). The data collected (in inches) is as follows: Month New Mexico Arizona January 0.02 February 0.94 March 0.87 April 0.31 May 0.2 June 0.28 July 1.93 August 2.24 September 1.22 October 0.22 November 0.67 December 0.02 Data Source: Construct a box plot and comment if the amounts of rain are similar to each other for the two areas for a year.

2) Calculate the following probabilities with the corresponding distribution:

• Normal Distribution, using a mean of 20 and standard deviation of 10:

− Find a = 12, not cumulative

− Find a = 23, cumulative

• Poisson Distribution, using a rate equal to 15:

− Find a = 14, not cumulative

− Find a = 19, cumulative

• Gamma Distribution, using a shape parameter of 5 and scale parameter of 2:

− Find a = 10, not cumulative

− Find a = 15, cumulative

3) We are conducting an experiment with different levels of factors and how they affect the height that a plant will grow. Each of the different scenarios are conducted twice, to help ensure more accurate results. The first factor that was looked at was the amount of yellow light, and had two levels, 50% and 60%.

The second factor that was considered was the amount of red light, and three levels were considered, 10%, 15%, and 20%. The last factor was the amount of blue light, 5%, 10%, and 15%. Any remaining light is filtered sun light. The observations that were witnesses are as follows: Yellow Light Red Light Blue Light Observations 50% 10% 5% 12, 10% 10% 14, 10% 15% 15, 15% 5% 12, 15% 10% 11, 15% 15% 13, 20% 5% 15, 20% 10% 16, 20% 15% 14, 10% 5% 10, 10% 10% 11, 10% 15% 15, 15% 5% 13, 15% 10% 12, 15% 15% 10, 20% 5% 14, 20% 10% 13, 20% 15% 14, 13

Using pivot tables, answer the following questions:

• What is the overall average of the observations?

• Regardless of the amount of yellow light, what is the average height if we use 15% red light and 5% blue light?

• What is the overall maximum value of the data?

• What is the overall minimum value of the data?

4) We are working for a company that builds machinery for mining. There are a certain number of factors that we use in order for us to sell the machinery. The company has been keeping track of the sales numbers for the past six months, and they would like a number of questions answered. The sales figures are as follows:

• August 2014 - $4,565,853.22

• September 2014 - $5,263,558.15

• October 2014 - $6,187,998.38

• November 2014 - $4,962,347.75

• December 2014 - $4,248,654.46

• January 2015 - $3,956,874.59

The amount of the money spent on different operations in the company are described as follows:

• Administrative Expenses are worth 10%

• Overhead (Rent, Utility Bills, etc.) are worth 15%

• Marketing gets a budget of 10%

• Employees earn a commission of 5% of the total sales

• The profit margin then becomes 60%

There is also an opportunity for our office to earn a bonus from the sales. However, the amount of the bonus is dependent on the amount of sales. The amount of bonus is calculated as:

• If sales are above or equal to $6,000,000, then a bonus of $100,000 is given

• If sales are below $6,000,000, but above or equal to $4,500,000, a bonus of $50,000 is given

• If sales are below $4,500,000, then no bonus is given

Hint: You are going to need to use two IF functions in one formula.

By using a what-if analysis, management wants to know, what do the following values need to change to if we are wanting to make a profit of $6,500,000? (It’s ok to put your answers on another spreadsheet)

a. If we are to change the profit margin percentage, what does it need to be?

b. If we are to change the administrative percentage, what does it need to be?

c. If we are to change the commission percentage, what does it need to be?

Paper For Above instruction

This comprehensive assignment covers various statistical and analytical tasks using Microsoft Excel, including data visualization, probability calculations, data analysis through pivot tables, and financial modeling. The tasks involve comparing rainfall data between New Mexico and Arizona, performing probability distributions, analyzing plant growth experiments, and conducting financial calculations related to sales and operational expenses, culminating in scenario analysis for profit optimization.

Rainfall Data Analysis and Visualization

The first task involves analyzing the monthly rainfall data for New Mexico and Arizona to determine if the annual precipitation amounts are similar. The data shows monthly rainfall in inches for Las Cruces (NM) and Tucson (AZ). The primary goal is to construct a box plot for both datasets to visually compare their distributions. Using Excel's built-in charting tools, such as box plot representations via the "Insert Box and Whisker Chart," allows for effective visualization. The box plot depicts the median, quartiles, minimum, and maximum values, which facilitate understanding the spread and symmetry of the data.

Once the box plots are generated, interpret the data to comment whether the rainfall patterns in the two regions are similar. Similar box plots with overlapping interquartile ranges, medians close to each other, and comparable ranges suggest similar rainfall distributions. Differences might indicate variability or skewness that can inform regional climate assessments.

Probability Calculations Using Distributions

The second task involves calculating probabilities using three statistical distributions: normal, Poisson, and gamma. For each distribution, specific parameters are provided.

In the normal distribution, with a mean of 20 and a standard deviation of 10, calculations include finding the probability density at a = 12 (not cumulative) and at a = 23 (cumulative). These calculations are performed using Excel functions like NORM.DIST, with the cumulative parameter set accordingly.

For the Poisson distribution, with a rate (λ) of 15, the probability of exactly 14 events (not cumulative) and up to 19 events (cumulative) are calculated using POISSON.DIST, adjusting the cumulative parameter.

Similarly, the gamma distribution with shape = 5 and scale = 2 is used to find the probability density at a = 10 and the cumulative probability up to a = 15, utilizing GAMMA.DIST.

Plant Growth Experiment Data Analysis

The third task involves analyzing plant growth data across different light conditions. The data set includes observations for various combinations of yellow, red, and blue light levels, with each combination tested twice. Using pivot tables, summarize the data to compute overall averages, conditional averages (e.g., for specific red and blue light levels), and minimum and maximum values.

Creating pivot tables in Excel involves selecting the dataset, inserting a pivot table, and setting the appropriate fields (e.g., Yellow Light, Red Light, Blue Light) as row or column labels and the observations as values. Calculations for overall averages, maximums, and minimums are straightforward once the data is summarized.

Financial Data Analysis and Scenario Planning

The final task involves analyzing sales and operation costs for a mining machinery company over six months. The available sales figures are used to compute total revenues and expenses, applying percentage-based costs for administrative expenses, overhead, marketing, and employee commissions. A profit margin of 60% is applied to determine profit levels.

Furthermore, a bonus calculation depends on whether total sales exceed certain thresholds, implemented with nested IF functions in Excel. Using the sales data, total profits are calculated, including the bonus if applicable.

Finally, a what-if analysis explores how changing key parameters affects the final profit. Adjustments are modeled by varying the profit margin percentage, administrative expense percentage, and commission percentage. These analyses guide strategic decisions and identify the necessary adjustments to achieve a target profit of $6,500,000.

Conclusion

This multi-faceted assignment leverages Excel's capabilities to perform data visualization, statistical analysis, pivot table summarization, and financial modeling. The integration of graphical and numerical tools provides comprehensive insights into regional climate patterns, probabilistic assessments, biological experiments, and operational profit planning, reflecting real-world analytical skills vital for data-driven decision-making.

References

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