The question and instruction is in the attached file
Instructions What is this code doing in R. Explain? #First code > X<- c(0.301,0.176,0.125,0.097,0.079,0.067,0.058,0.051,0.046)=""> Y<- c(1,="" 2,3,4,5,6,7,8,9)=""> Dev <- (y="" -="" mean(y))^2=""> Dev > sum(Dev*X) > stdv<-sqrt(sum(dev*x))> stdv #Second code > i <− c(1:5)=""> for (n in i) print(n * 10) #Third code > even <− 0=""> while(even < 10)="" {even=""><− even+ 2 + print(even)} using r use the datasets advertisement, sales transactions and incomeproject1 and assume that you are the analytics manager of the organization. you discovered that people in your company only make decisions based on the representation of the data. they do not believe in models that cannot understand but they believe in intuition and rational when they see data visualization. your role is to prepare a report that includes the visual helps to support the strategy of the organization. your organization is offering beauty products, you need to open operations in five different states and you know data about the income in different states, the same as the way that young people are using facebook (the dataset helps you to think about). people are buying products using different types of payment methods (your data about transactions only guide you to get a feeling on how people pay these days), and how people are exposed to advertisement of products in your industry. the tables are independent but with the data in each one, you can obtain some insights that can help you for designing the strategy. the most important in your report is to communicate your ideas to a group of people that will use visual analytics capacity. you need to create the story of the analysis. the problem for you is to demonstrate that with the data visualization process you can guide the strategy design process. remember, that you need to think that the purpose is to have several observations of the variables of the files and to try to provide insights for areas such as location, possible profits/sales, methods to contact potential customers, etc. remember that you need to explain the graphics that you generated. pay special attention to indicate how the graphics are providing insights for the decision. you need to present a report about the analysis of the datasets that includes a combination of tools and a content with minimum. think abut questions such as: 1. can you show differences in groups in the advertisement dataset? in the sales transactions dataset? describe at least two groups. you can select any variables 2. what are the min attributes of the groups that you selected in the previous question? 3. could you please review the advertisement file and using the expenditure variables as target? show the relationship to the other variables (a regression), compare the result of the regression and actual value. partition the data in two groups, do not worry about the number of sample points. create a graph for the differences between predicted and actual values. 4. using the incomeproject dataset. in this particular dataset you need to review the time series and look for insights regarding the states income, changes, trends, correlations, describing the best and worse states etc. 5. present insights that you can identify with the tools used and interpret the graphs under the context of the case and the story that you created. 6. summarize your visuals in two dashboards. including the most important aspects that you discovered in the whole process. you can use tableau for this part of the exercise. with this data and the other datasets you can infer some possible places to open the company’s operation. a preparation of interactive dashboard is a great bonus. variables of the advertisement files for project the study is about stereotypes regarding beauty products advertisement. the variable meaning is: · respondent: the subject / case / answer · gender age: age of respondent · education: education level · income: annual income · spending: amount (average) people pay for beauty and hygiene product · ad frequency: the number of advertisement messages that people think they see/hear per day · stereotype: this is how many of the ad messages describe a stereotype · reinforcing: this scale identifies the reinforcement of the gender stereotypes · transform: agreement about empowerment advertising (provide the users/consumers the choices to take actions) would help transform cultural gender stereotypes · empowerment %: this is the perceived percentage of empowerment advertising that people see/hear per day even+="" 2 ="" +="" print(even)}="" ="" using="" r="" use="" the="" datasets="" advertisement,="" sales="" transactions="" and="" incomeproject1="" and="" assume="" that="" you="" are="" the="" analytics="" manager="" of="" the="" organization.="" you="" discovered="" that="" people="" in="" your="" company="" only="" make="" decisions="" based="" on="" the="" representation="" of="" the="" data.="" they="" do="" not="" believe="" in="" models="" that="" cannot="" understand="" but="" they="" believe="" in="" intuition="" and="" rational="" when="" they="" see="" data="" visualization.="" your="" role="" is="" to="" prepare="" a="" report="" that="" includes="" the="" visual="" helps="" to="" support="" the="" strategy="" of="" the="" organization.="" your="" organization="" is="" offering="" beauty="" products,="" you="" need="" to="" open="" operations="" in="" five="" different="" states="" and="" you="" know="" data="" about="" the="" income="" in="" different="" states,="" the="" same="" as="" the="" way="" that="" young="" people="" are="" using="" facebook="" (the="" dataset="" helps="" you="" to="" think="" about).="" people="" are="" buying="" products="" using="" different="" types="" of="" payment="" methods="" (your="" data="" about="" transactions="" only="" guide="" you="" to="" get="" a="" feeling="" on="" how="" people="" pay="" these="" days),="" and="" how="" people="" are="" exposed="" to="" advertisement="" of="" products="" in="" your="" industry.="" the="" tables="" are="" independent="" but="" with="" the="" data="" in="" each="" one,="" you="" can="" obtain="" some="" insights="" that="" can="" help="" you="" for="" designing="" the="" strategy.="" the="" most="" important="" in="" your="" report="" is="" to="" communicate="" your="" ideas="" to="" a="" group="" of="" people="" that="" will="" use="" visual="" analytics="" capacity.="" you="" need="" to="" create="" the="" story="" of="" the="" analysis.="" the="" problem="" for="" you="" is="" to="" demonstrate="" that="" with="" the="" data="" visualization="" process="" you="" can="" guide="" the="" strategy="" design="" process.="" remember,="" that="" you="" need="" to="" think="" that="" the="" purpose="" is="" to="" have="" several="" observations="" of="" the="" variables="" of="" the="" files="" and="" to="" try="" to="" provide="" insights="" for="" areas="" such="" as="" location,="" possible="" profits/sales,="" methods="" to="" contact="" potential="" customers,="" etc.="" remember="" that="" you="" need="" to="" explain="" the="" graphics="" that="" you="" generated.="" pay="" special="" attention="" to="" indicate="" how="" the="" graphics="" are="" providing="" insights="" for="" the="" decision.="" you="" need="" to="" present="" a="" report="" about="" the="" analysis="" of="" the="" datasets="" that="" includes="" a="" combination="" of="" tools="" and="" a="" content="" with="" minimum.="" think="" abut="" questions="" such="" as:="" 1.="" can="" you="" show="" differences="" in="" groups="" in="" the="" advertisement="" dataset?="" in="" the="" sales="" transactions="" dataset?="" describe="" at="" least="" two="" groups.="" you="" can="" select="" any="" variables="" 2.="" what="" are="" the="" min="" attributes="" of="" the="" groups="" that="" you="" selected="" in="" the="" previous="" question?="" 3.="" could="" you="" please="" review="" the="" advertisement="" file="" and="" using="" the="" expenditure="" variables="" as="" target?="" show="" the="" relationship="" to="" the="" other="" variables="" (a="" regression),="" compare="" the="" result="" of="" the="" regression="" and="" actual="" value.="" partition="" the="" data="" in="" two="" groups,="" do="" not="" worry="" about="" the="" number="" of="" sample="" points.="" create="" a="" graph="" for="" the="" differences="" between="" predicted="" and="" actual="" values.="" 4.="" using="" the="" incomeproject="" dataset.="" in="" this="" particular="" dataset="" you="" need="" to="" review="" the="" time="" series="" and="" look="" for="" insights="" regarding="" the="" states="" income,="" changes,="" trends,="" correlations,="" describing="" the="" best="" and="" worse="" states="" etc.="" 5.="" present="" insights="" that="" you="" can="" identify="" with="" the="" tools="" used="" and="" interpret="" the="" graphs="" under="" the="" context="" of="" the="" case="" and="" the="" story="" that="" you="" created.="" 6.="" summarize="" your="" visuals="" in="" two="" dashboards.="" including="" the="" most="" important="" aspects="" that="" you="" discovered="" in="" the="" whole="" process.="" you="" can="" use="" tableau="" for="" this="" part="" of="" the="" exercise.="" with="" this="" data="" and="" the="" other="" datasets="" you="" can="" infer="" some="" possible="" places="" to="" open="" the="" company’s="" operation.="" a="" preparation="" of="" interactive="" dashboard="" is="" a="" great="" bonus.="" variables="" of="" the="" advertisement="" files="" for="" project="" the="" study="" is="" about="" stereotypes="" regarding="" beauty="" products="" advertisement.="" the="" variable="" meaning="" is:="" ·="" respondent:="" the="" subject="" case="" answer="" ·="" gender="" age:="" age="" of="" respondent="" ·="" education:="" education="" level="" ·="" income:="" annual="" income="" ·="" spending:="" amount="" (average)="" people="" pay="" for="" beauty="" and="" hygiene="" product="" ·="" ad="" frequency:="" the="" number="" of="" advertisement="" messages="" that="" people="" think="" they="" see/hear="" per="" day="" ·="" stereotype:="" this="" is="" how="" many="" of="" the="" ad="" messages="" describe="" a="" stereotype="" ·="" reinforcing:="" this="" scale="" identifies="" the="" reinforcement="" of="" the="" gender="" stereotypes="" ·="" transform:="" agreement="" about="" empowerment="" advertising="" (provide="" the="" users/consumers="" the="" choices="" to="" take="" actions)="" would="" help="" transform="" cultural="" gender="" stereotypes="" ·="" empowerment="" %:="" this="" is="" the="" perceived="" percentage="" of="" empowerment="" advertising="" that="" people="" see/hear="" per="">