LEADERSHIP DISCUSSION POST 1:The Changing WorldQuestion AReview and reflect on what you learned in the past 8 weeks. What is the most practical and easily applied lesson you learned? What was the hardest to grasp? Why? What else do you need to know about Measurement and Assessment Strategies?(HARDEST TO GRASP: FOLLOWERSHIP, EASIEST: LEADING TEAMS)Question BIs the world really changing faster today, or do people just assume so?HR MANAGEMENT DISCUSSON POST 2:Review and reflect on what you learned in the past 8 weeks.  Here are some starter questions to “get the ball rolling”…What is the most practical and easily applied lesson you learned?What was the hardest to grasp?  Why?  (LABOR RELATIONS)What else do you need to know about HRM?  Where are unionizing efforts focused today?  Do you agree with unions?  Why or why not?  Which concepts can you apply directly to your current work situation?

MANAGAMENT ASSIGNMENT – DUE MAY 10, 2021 11:59pm.Elizabeth Covington has brought Michael Ferrell to court. Elizabeth Covington is seeking to get her card back from Michael Ferrell or in the alternative Elizabeth wants to recover the true value of the card ($80,000?)You are Judge Wapner and you are presented with the following evidence.They say that "all good things must come to an end," and for Elizabeth Covington, the saying had unfortunately come true. After a brief illness, Elizabeth's husband Forrest had died at the age of sixty-eight. The couple had been happily married for forty-two years, and now Elizabeth was left with only her memories, and with the material belongings her husband had left behind. Her husband's funeral now complete, Elizabeth was faced with the responsibility of administering her husband's estate. As required by state law, she had only one year to "wrap up" the financial affairs of her husband's estate through the process of probate. The "clock was ticking" on the probate time limit, and Elizabeth knew that she must somehow "press on." As the sole heir of her husband's estate (Forrest had named his wife as the only beneficiary of his will,) all proceeds and property from the estate would pass to Elizabeth. That was little consolation to Elizabeth, as she would, if she somehow had the opportunity; trade all of her worldly possessions for another day with her life and soul mate.Some time ago, Elizabeth had read that one of the best way's to cope with the loss of a deceased spouse was to rid the house of the personal belongings of the lost loved one. Along those lines, she decided to have an estate sale. Elizabeth's daughter Samantha agreed to help with the sale, with the stipulation that all of the proceeds of the sale would be used for the benefit of her mother. Samantha knew that with her mother now approaching retirement alone (Elizabeth was sixty-five years old,) she would need all of the financial support she could muster.The date for the estate sale had arrived. All of Forrest's personal belongings had been arranged neatly in the garage. Throughout his life, Forrest had been an avid baseball fan and collector of baseball cards; although it had been his hobby, Elizabeth had not shared in his love for baseball or card collecting, so she therefore knew very little about the cards. Samantha did not know the difference between a "home run" and a ''touchdown." Forrest's entire baseball card collection was displayed in the garage with his other worldly possessions, waiting for buyers.Michael Ferrell, an eighteen-year-old who lived in the neighborhood, decided to attend the Covington estate sale. He arrived early that morning, before all other prospective customers, with a twenty-dollar, self-imposed spending limit. What first caught Michael's attention was Forrest's baseball card collection; more specifically, what appeared to be a 1952 Topps Mickey Mantle rookie baseball card in near-mint to mint condition. On the outside of the box containing the cards was a sticker indicating "All Cards $1 Each." Michael could not believe his eyes. He meandered for several minutes through Forrest's old dress shirts, golf clubs and electronic equipment, with butterflies in his stomach and with the Mantle baseball card in his hand. Michael debated with himself about whether he should disclose the real value of this treasure to Mrs. Covington (he had heard that a similar Mantle card had sold in 2006 for over $72,000!); remembering something about "discretion being the better part of valor," however, Michael paid Elizabeth the $1, left the estate sale, and returned home with his treasure.Later that month, Elizabeth was in her living room watching her favorite public television show, "Antiques Circus." To her surprise, her young neighbor Michael was on the show, asking an antiques expert to estimate the value of the 1952 Mantle card. The expert, well-trained in the art and science of baseball card collecting, said that even in a tough economy, the card would likely bring $80,000 at public auction. Elizabeth was heartbroken; not only had she sold her husband's personal belongings (which she had come to regret,) but she knew that this one card could have "paved the way" for a more financially secure retirement. If only she had known...Write out your decision and the reasoning underscoring your decision.Consider and include ALL legal arguments that could be raised by either side in this dispute regardless of whether you would win the argument. (CONTRACT FORMATION is the law you will need to consider to complete this assignment.)

5 slides powerpoint. Integrate the data analysis I have in hand using RStudio and excel into powerpoint slides. We analyze the freethrow percentage in NBA with few model to determine corelation and other models. Please put all the things we have into a few slides based on the instruction I will attach.If you know how to use Rstudio this should be a 10 min work for you.setwd("C:/Users/kaziz/Desktop")library(readr)Basketball <- read_csv("C:/Users/kaziz/Desktop/MKTG 480N Basketball analytics.csv")# to help generate correlation plotsinstall.packages("PerformanceAnalytics", repos = "http://cran.us.r-project.org")library(PerformanceAnalytics)# to help visualize correlation in colorinstall.packages("corrplot", repos = "http://cran.us.r-project.org")library(corrplot)#See some Descriptive statistics about our Basketball datasetsummary(Basketball)attach(Basketball) plot(Basketball$FTP,Basketball$AST)```{r, results='hide'}# Using the function chart.Correlation from "PerformanceAnalytics" package,# we can create a correlation matrix easily, much easier than built in functions# However, before that, we need to pick out the numerical variables# because we cannot run correlation matrix with categorical data or missing dataBasketball.num = sapply(Basketball, is.numeric) # label TRUE FALSE for numerical variablesnum = Basketball[,Basketball.num] # selecting only numerical variables```chart.Correlation(num)correlation = cor(num, use = "complete.obs")corrplot(correlation, type="upper")Basketball$Post= ifelse(Basketball$Pos=="PG",1,ifelse(Basketball$Pos=="SG",2,ifelse(Basketball$Pos=="SF",3,ifelse(Basketball$Pos=="PF",4,5))))```{r}# first load package "caTools"library(caTools)# based on probability 70% training data / 30% test data split.# We create an item variable called "indicator", where indicator = TRUE takes up 70% of dataindicator = sample.split(Basketball, SplitRatio = 0.7)# Extract out the data based on whether indicator variable is TRUE or FALSEtesting = Basketball[!indicator,] # getting 30% of the data as testingtraining = Basketball[indicator,] # getting 70% of the data as training# Attach training data firstattach(training)# To build a linear regression model, give this model a name "linear":linear = lm(FTP~ Post + FGP + `3PP` + AST + TRB+ TOV+BLK+`PS/G`+ MP)# To see the result of model:summary(linear)plot(linear)# To predict the gross of data from testing dataset using the linear model we builttesting$linear_prediction = predict(linear, newdata = testing)# To see the accuracy of prediction:accuracy = testing$linear_prediction - testing$FTPpercent = accuracy/testing$FTPmean(accuracy,na.rm = TRUE) # to see how much percentage away from the actual