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A Coffee Shop Consortium called High Star Cafeteria has hired your services as a manager to figure out what is happening to their revenue, given

A Coffee Shop Consortium called High Star Cafeteria has hired your services as a manager to figure out what is happening to their revenue, given that in January 2010 their total revenue was $5,293,605, whereas in January 2019 it was $5,521,126, which is a very slow increase in 10 years. The data is attached in an Excel File in this test. They are requesting your help to understand how price increases are affecting the quantity of coffee cups sold.

  1. A table with the descriptive statistics of the coffee cups sold in the 10 years, as well as an explanation of the descriptive statistics: what do you see? What are some of the key aspects of the descriptive statistics that help you tell a story about these 10 years in cups of coffee sold.
  2. A graph (whichever you want) to show visually what is happening to the revenue of High Star Cafeteria (you can even combine it with price per cup or cups of coffee sold graphs if you want, ultimately, I want you to provide visual understanding of what is going on).

Run a regression where you explain how price changes are affecting the quantity of cups sold. Please remember to include an explanation of the coefficients as well as an explanation of the t-statistics, the intercept, the R-Squared, and the F-Statistic.

jan 10$7.13742962$5293605
feb 107.138773046250792
mar 107.387687805669753
apr 107.387621685620986
may 107.388749526452774
jun 107.388623156359570
july 107.388770296468087
aug 107.388059225943675
sept 107.447152075319355
oct 10
7.44
7319635443973
nov 107.447543775610680
dec 107.447198845354139
jan 117.447182875342262
feb 117.448905966623810
mar 117.447180395340417
apr 117.447567085628016
may 117.448183216086265
jun 117.448600896396908
jul 117.447740285756831
aug 117.448334726198946
sept 117.567040185324138
oct 117.567526195691683
nov 117.567408185602438
dec 117.567103765372216
jan 127.567029225315849
feb 127.568278326260481
mar 127.566789225134347
apr 127.566913605228414
may 127.567921165990380
jun 127.567975546031505
jul 127.567122925386711
aug 127.567853595939277
sept 127.566823425160214
oct 127.567195705441747
nov 127.567380125581214
dec 127.567022785310976
jan 137.567180125429964
feb 137.568335616303802
mar 137.567029765316258
apr 137.567142325401378
may 137.567787975889653
jun 137.568211596210018
july 137.567329575542987
aug 137.568024826068770
sept 137.567355835562843
oct 137.567599915747429
nov 137.567487135662139
dec 137.567124795388121
jan 147.567153455409796
feb 147.568165886175444
mar 147.566952985258189
apr 147.567119135383843
may 147.567978156033473
jun 147.568184086189207
jul 147.567291785514409
aug 147.567834585924904
sept 147.567333725546126
oct 147.567378675580121
nov 147.567314095531280
dec 147.567174485425700
jan 157.567073915349644
feb 157.568319276291446
mar 157.566873015197711
apr 157.566960995264246
may 157.567775695880366
jun 157.567841975930491
jul 157.566972325272814
aug 157.568262146248241
sept 157.947301185795315
oct 157.947709106119101
nov 157.947847486228934
dec 157.947687116101647
jan 167.947532935979264
feb 167.949028037165997
mar 167.947524445972523
apr 167.947522935971323
may 167.948239196539859
jun 167.948753106947776
jul 167.947713046122226
aug 167.948538356777318
sept 168.317324456088448
oct 168.317417406165714
nov 168.317477216215428
dec 168.317141775936593
jan 178.316933985763874
feb 178.318304006902702
mar 178.316941625770225
apr 178.317236646015454
may 178.317901496568117
jun 178.317900106566961
jul 178.317033775846822
aug 178.317627816340620
sept 178.317015475831612
oct 178.317137975933438
nov 178.317225086005849
dec 178.316734295597880
jan 188.316819085668364
feb 188.317918036581863
mar 188.316621065503752
apr 188.316778965635012
may 188.317331086093964
jun 188.317479096216995
july 188.316877925717274
aug 188.317280586051980
sept 188.316864275705925
oct 188.316781005636710
nov 188.316736975600110
dec 188.316687905559314
jan 198.316641965521126
feb 198.317663126369968
mar 198.316460905370620
apr 198.316562435455024
may 198.317187855974900
june 198.317307246074147
jul 198.316641535520774
aug 198.317083435888103
sept 198.316514055414808
oct 198.316697435567237
nov 198.316745255606993
dec 198.316520355420042

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ANSWER a The descprtive statistics for the data is given by Price per cup Sold coffee cups Total revenue Mean 7819833 Mean 7462742 Mean 5827411 Standard Error 0034369 Standard Error 5414776 Standard E... blur-text-image

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