# Applying analytic techniques to business

In the last assessment, you were asked to prepare the first part of your analytics report by creating graphs and calculating some descriptive statistics. In this assessment, you will write your 4-6 page analytics report by interpreting those graphs and statistics, and explicitly connecting those interpretations to implications in the practical business context.

The first step in creating meaningful information from raw data is to represent the data effectively in graphical format and to calculate any required statistics. The second step is interpreting and explaining those graphs and statistics in order to apply them in the business context.

In the previous assessment, you were asked to create the first part of your analytics report by preparing graphs and calculating some descriptive statistics. In this assessment, you will complete your analytics report by interpreting those graphs and statistics, and connecting those interpretations explicitly to implications in the business context.

In business and applied analytics, oftentimes you are interested in drawing conclusions about a population of interest. However, it may not be feasible or practical to gather data on the entire population. In those cases, data is gathered from a sample or subset of the population. Analyses done on the sample are then used to draw inferences regarding the overall population; this mathematic process is referred to as inferential statistics. In this assessment, we begin discussing the topics of sampling and drawing inferences.

All the inferential statistical techniques and methods covered in this course are considered parametric techniques and require certain assumptions to be used and for the results to be reliable, many of which are assumptions about an underlying distribution. Nonparametric techniques require no assumption about underlying distributions and are often used when the assumptions of parametric techniques are not met. Although these are beyond the scope of this introductory course, they are a great option for additional reading and research.

Analytics projects often result in two distinct types of reports or summaries: one tailored to the executive level, which takes the form of a presentation, and the other, a detailed analytics report, which documents an analysis so thoroughly that another analyst can reproduce the analysis exactly. Many times, the latter type is referred to by other departments or analysts wishing to conduct a similar analysis on similar data or by the same analyst who wants to repeat the analysis on a new or revised set of data. In this assessment, you will learn the essential elements that should be included in a report at this level of detail and you will create your own analytics report addressing the business problem you have been working on.

#### Scenario

The first step in creating meaningful information to develop a business report for decision making. The business report includes the analyzed raw data, effectively presents the analysis results in text and graphical format, as well as calculate any required statistics.

The second step is interpreting and explaining the graphs and statistics to understand the impact in the practical business context.

In the last assessment, you were asked to create the first part of your business analytics report by introducing a company, analyzing company stock data, developing graphs, and calculating some descriptive statistics.

In this assessment, you will adjust your business report to minimize limitations of one year’s worth of data. You will use the same company for this assessment and you will use 5 years of data!

You will also enhance your introduction or business context section of your business report based on your new graphs and your interpretation of the data graphs and descriptive statistics over a five year period. Your interpretation efforts of graphs and descriptive statistics will explicitly connect in the conclusion area. Conclusions and recommendations are the final effort in the development of a practical business report and should be supported by citations. Remember that opinion is not allowed.

Your supervisor has asked you to prepare a report for the quarterly company meeting. The first part of the task was to download the data and create scatterplots and histograms, and to calculate mean, median, and mode of 5 years of stock prices for your report. Now you must analyze and interpret those graphical representations of the company stock and write the report of your findings and recommendations for your supervisor.

You are an analyst using the same company and five years of stock data. Having accessed the company data and placed it in an appropriate graphical format, you must now use descriptive statistics and analysis to develop a report to inform business decisions.

#### Instructions

After reviewing and integrating your instructor’s feedback on your previous Assessment, complete the report as follows:

• For each graph you created, write at least one well supported paragraph interpreting the graph: What does that graph represent? What does the shape of the graph tell you about how the data have changed over time?
• For each statistic you calculated, include at least two to three well-supported sentences explaining what the statistic represents:
• What does the mean tell you? How do you know?
• What does it imply if the median is different from the mean?
• What does the standard deviation tell you about the volatility of the data?
• Write a new conclusions section in which you explain how these interpretations can be used in the company:
• What are some trends about which company leaders should be aware?
• How might the information you have provided be used in decision making in the company?
• What are other analysts indicating about the stock?
• Explicitly connect other analysts’ comments and recommendations to your interpretations to possible impact to the business context
• Lastly, should your company invest of partner with the company or stock being evaluated?

Create a 4-6 page report containing:

• APA-formatted title page.
• 1-2 page introduction of your chosen company that you created in your previous assessment.
• Section labeled Graphical Representations of Data that includes the four graphs you created as well as your interpretations of the graphs.
• Section labeled Descriptive Statistics, with the statistics you calculated as well as your interpretations of the statistics.
• One-page conclusion in which you describe the potential business applications of the data and interpretations.
• APA-formatted references page (remember to cite the source of your financial data, analyst comments and support for your interpretations).

Example Assessment: You may use the following to give you an idea of what a Proficient or higher rating on the scoring guide would look like:

Copyright ©2019 Capella University. Copy and distribution of this document are prohibited.

Learner’s Name

Capella University

April, 2019

APPLYING ANALYTIC TECHNIQUES TO BUSINESS 2

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Microsoft Corporation

Microsoft is one of the world’s leading IT firms. With constant growth in its offerings,

Microsoft currently develops and licenses computing software, services, devices, and solutions

worldwide (Yahoo Finance, 2019). Some of Microsoft’s prominent offerings include Microsoft

Windows, which constitutes 35.5% of the market share for operating systems as of March 2019

(StatCounter, 2019), Office 365 Commercial Products and Services, available through cloud

technology, and Microsoft Azure, a cloud platform for data storage and analysis (Yahoo Finance,

2019).

Although software has been the basis of Microsoft’s success previously, in 2013, under

the leadership of Steven Anthony Ballmer, the company announced a shift in focus toward the

production of devices and services (Belanger, 2018). Consequently, there was an increased in

production of phones, tablets, personal computers, and gaming hardware including as Xbox. This

shift, however, was unsuccessful, largely because Microsoft’s strategic acquisition of all of

Nokia’s Devices and Services business proved a significant failure (Belanger, 2018).

The change in leadership from Ballmer to Satya Nadella in 2014 redirected the company

to profitable growth with a shift in focus toward business technological services and cloud

computing (Belanger, 2018). The acquisition of LinkedIn, the development of Office 365, and

the launch of Microsoft Azure generated significant profits for the company in the recent years

(Belanger, 2018). For the past 5 years, Microsoft leadership has witnessed an average growth

rate of 1.4%, and the company leaders are optimistic about generating a 7.5% increase in profits

in 2020 (Simply Wall ST, 2019). What makes Microsoft’s future really promising is its current

standing; Microsoft generated a revenue of close to 32.5 billion U.S. dollars and a profit of 8.6

APPLYING ANALYTIC TECHNIQUES TO BUSINESS 3

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billion U.S. dollars owing to a 76% increase in the sales of Azure and a 39% increase in sales of

surface tablets and laptops (Weise, 2019).

Graphical Representations of Data

Interpreting the Scatterplots

Figure 1.1. Scatterplot of highest stock prices of Microsoft based on data from Yahoo Finance
(2019)

Figure 1.1 depicts the trend in the highest stock prices of Microsoft from February 2018

to February 2019. The graph explains the relationship between two variables: highest stock

prices (in U.S. dollars) on the y-axis, which is the dependent variable, and time (in days) on the

x-axis, which is the independent variable. The scatterplot is linear: The highest stock prices show

an approximately positive relationship with time in 2018. The highest stock prices for Microsoft

increased in value in 2018. However, the relationship is moderately strong, as there is no

significant increase in the value of the highest stock prices with time and there have been small

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drops in prices toward the end of 2018 and subsequent rises in February 2019. There is a

noticeable absence of significant outliers.

Figure 1.2. Scatterplot of lowest stock prices of Microsoft based on data from Yahoo Finance
(2019)

Figure 1.2 presents the trends in Microsoft’s lowest stock prices from February 2018 to

February 2019. The graph depicts the relationship between lowest stock prices (in U.S. dollars)

on the y-axis, the dependent variable, and time (in days) on the x-axis, the independent variable.

The scatterplot presents a moderately positive relationship between the lowest stock prices and

time. The value of the lowest stock prices increased for approximately seven months from March

to October, with small drops and recoveries between October and December. The scatterplot

takes a positive linear form with a small slope, indicating low volatility in the lowest stock

prices. The scatterplot also helps us understand that there are no significant outliers, which

confirms the stability of Microsoft’s market shares.

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APPLYING ANALYTIC TECHNIQUES TO BUSINESS 5

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Interpreting the Histograms

Figure 2.1. Histogram of adjusted closing stock prices of Microsoft based on data from Yahoo
Finance (2019)

Figure 2.1 presents the number of occurrences of daily adjusted closing stock prices

falling within equally distributed continuous data ranges. The ranges of adjusted closing stock

prices are marked on the x-axis, and the number of occurrences of prices falling within the

ranges of adjusted closing stock prices is marked on the y-axis. The histogram is skewed to the

left; that is, a majority of the data points fall within the higher ranges of daily adjusted closing

stock prices. This indicates that the histogram is negatively skewed with the median being

greater than the mean, indicating volatility in the adjusted closing stock prices of Microsoft in the

market.

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Figure 2.2. Histogram of stock volume of Microsoft based on data from Yahoo Finance (2019)

Figure 2.2 presents the number of occurrences of Microsoft’s daily stock volumes being

bought or sold within continuous data ranges. The ranges of stock volume are marked on the x-

axis, and the number of occurrences of stock volumes falling within the ranges is marked on the

y-axis. The histogram is skewed to the right, indicating that a majority of the daily stock volume

data points fall within the lower ranges of the stock volume. This indicates that the histogram is

positively skewed with the mean being greater than the median. With 80% of the data points

falling within the lower ranges of stock volume, the histogram is strongly skewed to the right,

indicating unequal distribution and difficulty in speculating the daily stock volume of Microsoft.

Descriptive Statistics

Mean, Median, and Standard Deviation of Adjusted Closing Stock Prices

The mean, or the average value of a data set, of Microsoft’s adjusted closing stock prices

is 101.939 U.S. dollars, indicating the healthy market standing of Microsoft’s stock. It is

indicative of the company’s stable growth in revenue and profits throughout the year.

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While mean is the average value of a data set, median is the data point that corresponds to

the middle value in the data set. The median for Microsoft’s adjusted closing stock prices is

103.249 U.S. dollars, which is greater than the mean, indicating the presence of outliers on the

lower side of the stock prices; this highlights the prevalence of fluctuations in Microsoft’s stock

value. This difference in mean and median also indicates asymmetry in the distribution of values

for adjusted closing prices. The standard deviation for the adjusted closing stock prices is 6.953

U.S. dollars; considering that the average stock price is 101.939 U.S. dollars, the volatility is

6.7%. The standard deviation is representative of the volatility in the stock pricing and, therefore,

helps understand the level of risk involved in investing in a stock. The standard deviation

suggests the prevalence of moderate risk in purchasing Microsoft’s shares.

Mean, Median, and Standard Deviation of Daily Traded Stock Volume

The mean of Microsoft’s daily traded stock volume from February 2018 to February

2019 is 31,210,598, which is indicative of the high liquidity of the company’s stock (Seth, 2018).

Considering that a stock that is traded at fewer than 10,000 shares each day is deemed a low-

volume stock (Seth, 2018), Microsoft’s daily traded stock volume is representative of a large

number of prospective buyers and, therefore, a highly valuable publicly traded firm. The median

for the stock volume is 28,123,200, which is less than the mean. This indicates the presence of

outliers on the higher side of the data set and, therefore, shows that the company has significant

spikes in its daily tradable stock volume. The standard deviation is found to be 12,909,909.8,

which is equivalent to 41.3% of the mean for stock volume. A standard deviation of

12,909,909.8 is representative of high volatility in the data set, which shows a considerable lack

of consistency in the volume of Microsoft’s stock.

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Conclusion

The graphical representations and statistical calculations of Microsoft’s stock history

gives valuable insights that could help management make decisions about the launch of new

products and expansion. Some important trends that leaders should be aware of are as follows:

• While there is a gradual rise in the highest and lowest stock prices for the second and

third quarter, the fourth quarter is characterized by moderate falls and recoveries in the

highest and lowest stock prices;

• More than one fourth of the adjusted closing stock prices fell within the high-value range

of 105 to 110, which is a signal of high demand;

• A volatility of 41.3% for daily traded stock volume indicates great unpredictability in the

exchange rate of Microsoft’s stock. High volatility in stock volume usually indicates

unexpected earnings by a firm or the dissemination of good or bad news about the

firm/industry in the market (Morah, 2018).

Awareness of trends in stock prices may help management decide to launch products or

upgrade offerings in the early and later parts of the year, which may create hype and push sales

during these periods; this may facilitate a further increase in gross revenue and profits during the

stable periods of the third and fourth quarters. The histogram for adjusted closing stock prices

shows that a large number of data points fall within the high-value range of 105 and 110 U.S.

dollars with significant stock volume exchanged daily. This may inspire management to double

stock volume by halving stock prices, which may help increase the demand for the stock and,

therefore, improve market capitalization for the company.

The scatterplots for the highest and lowest daily stock prices indicate a positive linear

correlation between time and stock value, which helps understand the impact of the improved

APPLYING ANALYTIC TECHNIQUES TO BUSINESS 9

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growth in Microsoft’s revenue in 2018 compared with preceding years. The scatterplots also

indicate better valuation of prices in the start of 2019 than in 2018; this demonstrates the impact

of the company’s quarterly performance, namely generating 32.5 billion U.S. dollars in revenue,

on its market valuation at the start of 2019. Interpreting the histograms helps understand that

while the median for adjusted closing stock prices was relatively on the higher range of the data

set, the median for stock volume was on the lower range of the data set, reflecting high demand

for Microsoft’s stocks and, at the same time, a reservation on the part of Microsoft’s

shareholders to sell. This trend coincides with the fact that Microsoft, during the period,

improved in its distribution of dividends (Weise, 2019), which could be why the rate of change

in Microsoft’s traded volume was lower than the rate of change in its stock pricing.

APPLYING ANALYTIC TECHNIQUES TO BUSINESS 10

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References

Belanger, L. (2018, April 4). 10 amazing moments in Microsoft’s history, from its founding to

https://entrepreneur.com/article/311468

Morah, C. (2018, March 2). Are stocks with large daily volume less volatile? Retrieved from

stocks.asp

Simply Wall St. (2019). Microsoft Corporation (NASDAQ: MSFT): What does the future look

msft/microsoft/news/microsoft-corporation-nasdaqmsft-what-does-the-future-look-like/

http://gs.statcounter.com/os-market-share

Weise, K. (2019, January 30). Releasing earnings, Microsoft stays in stride, with cloud powering

https://nytimes.com/2019/01/30/technology/microsoft-

earnings.html?rref=collection%2Ftimestopic%2FMicrosoft%20Corporation

https://finance.yahoo.com/quote/msft/profile/

5

Using Analytic Techniques to Add Meaning to Data

Students Name

Professor’s Name

Course

Date

Nike Company Stock Price

Introduction

As the world’s largest athletic apparel entity, Nike is one of the leading footwear, equipment and apparel corporation globally. It was founded as a Blue Ribbon Sport in 1964 and became the Nike it is today in 1971 after the victory Greek goddess. The term Nike was derived from the Greek name Greek goddess of victory, which, since it was established, has experienced numerous achievements in the footwear market. It has grown to be one of the most successful sports businesses in the world and currently employs more than 76000 individuals across all its operational stores globally (Yao & Chen, 2019). The entity offers its products through its Nike brand and its subsidiaries, including the Converse and Jordan brands. It sponsors the most significant sports and athletes teams across the globe, including Serena Williams, Alex Morgan, LeBron James and Rafael Nadal. Nike Company, as the most recognizable sports brand in the world, manufactures, markets and sells sports-related products to the global market. The organization is headquartered in Oregon near Beaverton and within the metropolis of Portland. Following its fiscal year ending May 2022, the company made more than \$44.54 billion in revenue. Its brand currently stands at the value of \$32 billion, representing the most valuable sportswear business in its industry.

Marketing Mission and Vision

Generally, the one company that is more likely to appear in one’s mind when it comes to sports products like shoes is Nike. Its strong mission statement has dramatically contributed to establishing the entity’s brand in people’s minds. It has aligned its mission and vision statement with its primary goals and strategies. Its mission statement can be described by three main aspects: creating innovation and inspiring and supporting athletes globally. The company’s mission statement is “to bring inspiration and innovation towards every athletes in the globally (Wondershare, 2021).” On the other hand, the company’s vision statement is “to remain the most authentic, connected and distinctive brand ever.” It uses inspirational words like “everyone with a body is an athlete,” which aligns with its mission. Such inspirational phrases or messages enhance its sales in the local and global markets. The company’s marketing plan transverses numerous guidelines and objectives on timelines. Through its marketing strategies, the company reported that it targets to increase its annual profits by 10 percent in the current year. This is a 25 percent raise in return on invested capital, raising its dividends to 35 percent (Freixo, 2023). The vision of Nike is based on creating innovative thinking in product manufacturing and enhancing its athlete’s abilities. In other words, the company aims to manufacture innovative products that put its brand ahead of advanced technology and innovation strategies. Nike’s products are often targeted toward athletes and sports events.

Sales

Nike has experienced consistent fluctuations in sales and revenue over the past few years. Following the most recent annual report, the company collected more sales and revenues in the first and fourth quarters than in the second and third quarters. The company’s sales and revenues were often made from its numerous products related to sports and also non-sporty items. It has attained flexibility associated with demographic changes, trends, preferences and styles. Based on recent past years, the company recorded a total revenue of \$39.12 billion, \$44.53 billion and 46.71 billion in 2020, 2021 and 2022, respectively. Following the revenue trend over the recent past periods, the company has consistently improved sales. It faced a significant decline in 2020 due to the impact of covid-19.

Having operated more than 122 footwear entities across 12 countries, Nike is surrounded by stiff competition pressure from rival companies like Adidas, Reebok, Converse, Fila and Puma. Nevertheless, the company has taken significant steps to remain on top of its main competitors. One of the approaches used by the company has been cost management. The company’s manufacturing operations and activities are often conducted outside the United States. This is a competitive advantage for the entity as it operates in countries where production costs are low. Lowering production costs helps the company widen its profitability margin, maximizing its profits. Other competitive advantages that hold the company at the top position include its famous and well-established brand, strong social media followers and international popularity.

Graphical Representation of Data

Scatterplot of the Highest Stock Price

Data and high columns were selected to prepare the scatterplot for the company’s highest stock price. On the Excel tab, click insert, followed by the option of the scattered graph under the chart slot. After clicking ok, a pave will open, and it is here where the scatterplot is generated. The title is then formatted based on the company’s values and the labelled axis. After completing the graph, it was copied from the Excel file and pasted into the word file.

Scatterplot of the Lowest Stock Price

When developing the scatterplot of the lowest stock price for the company, date and low columns were selected. The insert option is clicked on the Excel tab, and the scatterplot option under the charts slot is selected. After clicking the scatterplot option, a pave gets opened, and it is here where the scatterplot is generated, formatted and labelled. The complete scatterplot is then copied from the Excel file and pasted into the word document.

Histogram of the adjusted daily closing stock price

When creating the adjusted daily closing stock price histogram, the adjusted close columns were selected in the dataset. The insert option was clicked on the Excel commands tab, followed by the histogram option under the charts slot. This opened a pane where the histogram was then generated. The title is then formatted, and the axis is labelled. Besides, the gridlines and tick marks are removed, after which the graph is copied from the Excel file and pasted into the Word document.

Histogram of the stock trading volume

When developing the company’s stock trading volume, the volume column in the data set was selected. On the excel command tab, insert option was clicked followed by the click on the histogram option. The pane was opened after clicking on the histogram option where the histogram was generated to its completion. The complete graph was then copied and pasted from the excel file to the word document.

Descriptive Statistics

Some of the significant elements included in the descriptive statistics included the mean, mode, median and the standard deviation related to the adjusted daily price of the company’s daily closing.

 Statistic Value Adj Close Mean 105.6364523 Standard Error 1.16804876 Median 100.656334 Mode 126.129288 Standard Deviation 18.54219923 Count 252

In creating the descriptive statistic table, the data analysis tool was clicked in the Excel workbook tab. The first dialogue box was opened up, where the descriptive statistics were chosen. This was by clicking, which was followed by another dialogue box that popped up. This was utilized in selecting the data whereby the adjusted close data were highlighted. The option of summary statistics was established, followed by the output generation.

Calculation of the mean, median, mode, and standard deviation of the company’s stock volume

 Statistic Value Volume Mean 7399826.98 Standard Error 276910.943 Median 6158300 Mode 2985700 Standard Deviation 4395824.94 Count 252

This was developed by clicking on the data analysis tool in the Excel workbook tab. The first dialogue box popped up, followed by clicking the descriptive statistics. This was also followed by another dialogue box which popped up later. This was utilized in selecting the data whereby the column with the volume values was chosen from the dataset.

Discussion

The first and second graphs were based on the lowest and highest stock prices of Nike Company. As illustrated from the charts, Nike’s stock prices were lowest at the beginning of the year but later inclined at the year-ending period. The possible factor that led to the pattern is the most recent covid-19 pandemic that significantly affected its operations. Besides, the company’s adjusted stock prices conformed to a uniform distribution pattern, but the volume distribution skewed to the left. This showed that the company’s stock volume was decreasing during the year. Moreover, the company’s adjusted daily stock scored a mean of 105.64, while its standard deviation was 18.54. Further, the analysis showed that Nike’s daily stock volume had a mean of 7399826.98, while its standard deviation was 4395824.94. This was considered to be a relatively high value of standard deviation.

References

Freixo, M. C. (2023).
Valuation of Nike Inc (Master’s thesis).

Yao, D. W., & Chen, X. (2019).
Nike inc.-footware and apparel (Doctoral dissertation).

The highest stock price

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93.139999000000003 94.980002999999996 93.82 91.68 89.389999000000003 86.739998 88.400002000000001 84.629997000000003 78.489998 78.199996999999996 72.970000999999996 73.330001999999993 68.330001999999993 72.709998999999996 74.059997999999993 66.879997000000003 72.660004000000001 83.489998 86.860000999999997 85.739998 85.959998999999996 85.730002999999996 81.180000000000007 81.599997999999999 79.790001000000004 85.040001000000004 88.870002999999997 85.769997000000004 87.389999000000003 85.989998 87.769997000000004 85.879997000000003 86.529999000000004 90.25 89.440002000000007 86.900002000000001 89.440002000000007 89.529999000000004 89.120002999999997 89.870002999999997 90 .709998999999996 91.389999000000003 88 86.110000999999997 85.800003000000004 88.529999000000004 88.690002000000007 90.239998 90.639999000000003 91.419998000000007 91.669998000000007 87.739998 86.580001999999993 87.230002999999996 91.599997999999999 93.82 93.860000999999997 94.379997000000003 94.650002000000001 97.43 99.989998 100.69000200000001 99.25 99.779999000000004 100.879997 104.550003 103.900002 104.69000200000001 104.300003 103.769997 103.150002 98.989998 97.800003000000004 98.080001999999993 101.339996 100.239998 99.419998000000007 99.980002999999996 99.540001000000004 102.220001 101.849998 101.68 98.779999000000004 96 98.300003000000004 98.720000999999996 99.660004000000001 100.029999 99.550003000000004 98.980002999999996 98.910004000000001 98.050003000000004 98.940002000000007 97.25 99.040001000000004 98.230002999999996 97.230002999999996 96.349997999999999 99 98.989998 100.18 99.360000999999997 98.400002000000001 97.470000999999996 97.550003000000004 97.230002999999996 97.650002000000001 99.290001000000004 97.949996999999996 101.25 101.18 101.910004 106.83000199999999 107.33000199999999 105.889999 106.989998 106.779999 106.5 107 109.69000200000001 108.739998 109.769997 112 112.279999 112.089996 112.790001 112.66999800000001 112.519997 114.900002 117.410004 116.900002 113.75 113.839996 116.209999 118.230003 119.25 119.93 120.480003 119.69000200000001 118.550003 117.910004 114.05999799999999 117.199997 130.38000500000001 127.540001 124.75 126.19000200000001 127.099998 127.279999 127.730003 126.800003 128.5 130.44000199999999 130.41000399999999 130.929993 131.19000199999999 131.33999600000001 129.86999499999999 129.60000600000001 129.10000600000001 130.19000199999999 129.779999 129.89999399999999 131.38000500000001 130.259995 130.60000600000001 129.61999499999999 129.490005 126.400002 124.19000200000001 123.660004 124.099998 125.5 128.929993 130.41000399999999 129.91000399999999 136.35000600000001 130.11999499999999 129.800003 127.839996 128.60000600000001 130.320007 132.60000600000001 133.979996 132.11000100000001 133.529999 134.88999899999999 135.990005 135.800003 136.13000500000001 135.28999300000001 136.5 136.320007 137.949997 137.39999399999999 138.86000100000001 140.44000199999999 140.570007 139.13999899999999 138.13999899999999 139 139.44000199999999 140.490005 140.740005 141.13999899999999 147.949997 143.470001 143.60000600000001 142.19000199999999 142.91999799999999 143.05999800000001 142.61000100000001

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92.620002999999997 91.989998 88.5 85.150002000000001 87.910004000000001 90.57 90.839995999999999 89.940002000000007 85.879997000000003 80.919998000000007 82.879997000000003 82.07 73 71.760002 63.369999 62.400002000000001 60 64.150002000000001 67.199996999999996 60.580002 64 76.199996999999996 80.010002 79.510002 81.5 82.400002000000001 78.529999000000004 77.160004000000001 77.910004000000001 81.209998999999996 84.029999000000004 83.610000999999997 85.160004000000001 84.139999000000003 85.480002999999996 83.709998999999996 84.550003000000004 88.360000999999997 87.519997000000004 85.089995999999999 86.419998000000007 87.260002 87.650002000000001 87.309997999999993 88.6299970000000 03 87.830001999999993 86.510002 84.809997999999993 84.309997999999993 86.029999000000004 87.43 88.379997000000003 89.589995999999999 89.139999000000003 88.150002000000001 85.199996999999996 84.110000999999997 84.879997000000003 89.879997000000003 90.82 92.699996999999996 92.370002999999997 93.349997999999999 95.279999000000004 97.620002999999997 98.25 96.93 97.889999000000003 98.82 101.120003 100.470001 102.129997 102.709999 102.43 101.709999 94.879997000000003 94.739998 93.440002000000007 97.720000999999996 98.889999000000003 97.849997999999999 95.779999000000004 96.019997000000004 100.709999 98.089995999999999 98.800003000000004 93.57 93. 699996999999996 95.639999000000003 97.110000999999997 98.019997000000004 99.040001000000004 96.919998000000007 96.959998999999996 96.370002999999997 95.720000999999996 96.260002 95.510002 97.309997999999993 97.040001000000004 96.040001000000004 95.110000999999997 96.099997999999999 97.910004000000001 97.720000999999996 97.699996999999996 96.889999000000003 96.160004000000001 96.300003000000004 95.800003000000004 96.300003000000004 97.82 96.550003000000004 97.080001999999993 100.029999 99.889999000000003 102.400002 104.860001 103.379997 105.199997 105.459999 105.120003 105.470001 107.349998 107.349998 107.75 109.900002 111.089996 111.290001 110.5 110.57 111.139999 111.83000199999999 114.5 112 110.209999 110.540001 112.83000199999999 114 116.41999800000001 118.16999800000001 119.18 118.160004 115.800003 114.489998 111.739998 112.849998 125.260002 123.300003 122.269997 123.889999 123.959999 125.160004 125.30999799999999 123.589996 126.449997 127.269997 128.25 129.509995 129.33000200000001 129.259995 127.959999 127.010002 126.110001 127.550003 127.050003 127.720001 128.449997 128.86000100000001 128.64999399999999 126.68 127.900002 121.040001 121.150002 118.800003 121.099998 123.19000200000001 125.260002 128.46000699999999 128.35000600000001 128.770004 126.25 127.18 125.629997 126.83000199999999 127.370003 129.11000100000001 131.529999 129.929993 131.91000399999999 133.08999600000001 134.21000699999999 133.61999499999999 133.33999600000001 132.69000199999999 134.75 134.66999799999999 135 135.63999899999999 136.800003 137.64999399999999 138.270004 137.240005 136.229996 136.199997 137.25 137.46000699999999 138.75 137.16999799999999 142.509995 141.08999600000001 141.699997 141.10000600000001 141.03999300000001 140.429993 140.66000399999999

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