Active Listening in 4 Steps Essay Example for Free

Active Listening in 4 Steps Essay Active listening in 4 steps: The best managers make the best listeners Managers spend a good part of their workday listening to other people. But bear in mind, there’s a big difference between â€Å"passive† and â€Å"active† listening. Effective listening includes a four-step process to ensure understanding: 1. Listen to the total message.  2. Prove your understanding by using nonverbal signals. 3. Use open-ended probes. 4. Paraphrase what you hear. Motivating employees through realistic deadlines: 4 dos and donts Without deadlines, employees flounder. They can’t be aware of the urgency or priorities of a project unless their supervisors tell them. Following are four tips on motivating employees by setting realistic deadlines: 1. Do be specific  Name the target day and time. And mean what you say. If you ask for completion â€Å"next week,† don’t complain on Friday that you really needed it on Wednesday. 2. Do clarify priorities Let people know if this assignment takes precedence over any other projects they’re working on now. Avoid the old, favorite deadline â€Å"ASAP,† which usually translates in an employee’s mind as â€Å"whenever it gets done.† 3. Don’t set false deadlines  Setting a deadline earlier than necessary (because you don’t trust your employees to meet the real deadline) creates more problems than it solves. Your staff will soon learn that’s how you operate and will assume there’s always air in the schedule. As a result, they’ll always miss that first deadline, just as you knew they would. 4. Do establish an update schedule  The best-laid plans can go astray, and so can deadlines. You’ll minimize the chance of this occurring by setting up a progress report schedule when you assign the project. This is especially important for long-term projects. Motivating employees to do their best each day: 6 office communication techniques Here are six tips for motivating employees to stay on task and work together toward the common goal, according to a report by OnPoint Consulting: 1. Clarify, clarify, clarify.  2. Establish clear expectations. 3. Don’t micromanage your entrepreneurial-minded employees. But do monitor them. 4. Encourage employees to share bad news with you. 5. Solve problems quickly, but not too quickly. 6. Encourage informal and spontaneous interaction. Managing employee retention: Listen for subtle whispers of employee turnover Most good employees don’t stand up one day and quit out of the blue. They send off subtle hints that, if you’re listening, you can act on before the good employee walks out the door. That’s why it’s important to listen to statements like these that can act as an â€Å"advance warning system† for employee turnover: * This job isn’t what I thought it would be. Rather than exploring what the employee was originally told or trying to defend miscommunication, focus on the present. Ask, â€Å"How do you want your job to be?† * I’m at a plateau. I can’t grow here. Consider that a plea for job stimulation. Provide the employee with new responsibilities, cross-training opportunities or exposure to influential mentors. * I don’t get any feedback. Most employees crave regular input from their supervisors. Don’t leave them in the dark. Plan regular sessions to discuss ongoing projects and performance. * This place has too much politics. While you may not be able to eliminate all dissension and politics in the organization, you can level with the employee. If someone makes this complaint, address rumors head-on, a nd don’t play favorites. Maintaining workplace productivity: 7 common employee gripes (and how to silence them) A recent study says that 40% of managers in the United States are considered â€Å"bad bosses† by their employees. Yet most managers assume that their relationships with their employees are running smoothly. Obviously, some of those bosses are wrong †¦ and that can create major problems for workplace productivity. A Gallup Poll says organizations are 50% less productive—and 44% less profitable—when serious boss-employee conflicts exist. Employee retention strategies: 8 little things managers can do to retain the best When good employees leave for greener pastures, it makes a manager’s job much more difficult. Managers can prevent this syndrome by doing what they can to make their own pasture the greenest. While compensation helps, it’s not always cash that makes pastures greener. When salaries are equal with the marketplace, other factors take priority. Here are eight easy-to-plant â€Å"seeds† that help keep employees growing and content, according to a KEYGroup report: 1. Keep them engaged. Consider ways to provide opportunities for employees to improve on their skills or learn new skills they can use in their jobs. 2. Give praise where praise is due. Recognizing a job well done isn’t an expensive proposition, but it will mean the world to your employee. 3. Be aware of employees’ changing needs. By recognizing their changing needs, you show sensitivity to what’s going on in their lives. This builds loyalty and helps bring stability to their personal lives, which means they can focus better at work. 4. Realize that great employees thrive under great leaders. Employees won’t leave for greener pastures unless you drive them. The buck starts and stops with their leaders. 5. Conduct regular â€Å"stay† interviews. Rather than exit interviews, use regular â€Å"stay† interviews to provide an opportunity to compliment high performers on their work and inspire them to do more. 6. Create an environment where people can do their best work. By allowing employees to develop and implement their own ideas, you’ll keep them passionate about their work. 7. Create an environment of trust. Employees are happier and work harder when they trust their leaders. They decide which leaders they can trust based on how their fellow employees, company vendors and customers are treated. 8. Rid your pasture of weeds. The weeds are those poor performers and negative employees who stifle the good attitudes and high performance of their co-workers. The bottom line: Striving to keep employees happy and engaged is not just a â€Å"nice† thing to do — it’s the only way to maximize workplace productivity. Thoughtful employee retention strategies are useful not just for retaining people to avoid the high cost of recruitment. Engaged employees are creative, productive, motivated and brimming with good ideas

Donald Trump as a Presidential Candidate Essays -- Trump Should NOT Be

Due to Donald Trump’s lack of political experience, preoccupation with multiple careers, and blatantly self-serving intentions, he should not ever have been considered a reasonable candidate for the presidential election. First of all, Donald Trump is a businessman-not a politician. He received his degree in Economics/Real Estate from the University of Pennsylvania’s Wharton School of Finance. In 2007, Forbes Magazine reported his annual earnings in entertainment alone to be $32 million. This would have meant a significant pay cut, had he become United States President. Currently, he is the producer and star of â€Å"The Apprentice,† which has been on air since 2004 (â€Å"The Apprentice†). He holds multiple offices at the Trump Organization, and is also a chairman of Trump Hotels and Casino Resorts, Incorporated (Project Vote Smart). Donald Trump has put his name on products and companies both successful and unsuccessful, including food products, corporations, and a clothing line. Trump once stated that â€Å"The stuff that’s been sent over from China falls apart after a year and a half. It’s crap.† Ironically, the majority of his products are manufactured i n China (Webley, 8). How can we expect a man to keep in touch with an entire country when he can hardly keep in touch with his own business? Donald Trump has had some other losses in business as well, including a failed airline business and multiple bankruptcies in his casinos, among other lost investments. (Webley, 3). This may not have been so damaging, if only Donald Trump had any political experience whatsoever, but he has none (Project Vote Smart). Karl Rove, former President Bush’s chief political advisor, once said that being the President of the United States may b... ...lirtation Meant for "The Apprentice" Ratings? - Political Hotsheet - CBS News." Breaking News Headlines: Business, Entertainment & World News - CBS News. CBS, 19 Apr. 2011. Web. 17 May 2011. DiGiacomo, Frank. "President Trump? The Donald Swapped Party Affiliations for Potential Presidential Bid in 2009." Featured Articles From The New York Daily News. New York Daily News, 15 Feb. 2011. Web. 15 May 2011. Gelman, Andrew and Gary King, â€Å"Why Are America Presidential Election Campaign Polls So Variable When Votes Are So Predictable?† 1993. PDF. Rove, Karl. â€Å"What Makes a Great President.† Lecture. Rocco C. Siciliano Forum, Univ. of Utah. 13 Nov 2002. History News Network. George Mason Univ.’s History News Network, 30 June 2003. Web. 08 May 2011. Webley, Kayla. "Trump Airlines - Top 10 Donald Trump Failures - TIME." TIME.com. Time, 29 Apr. 2011. Web. 15 May 2011.

Answers for Wooldridge

MULTIPLE REGRESSION After completing this chapter, you should be able to: understand model building using multiple regression analysis apply multiple regression analysis to business decision-making situations analyze and interpret the computer output for a multiple regression model test the significance of the independent variables in a multiple regression model use variable transformations to model nonlinear relationships recognize potential problems in multiple regression analysis and take the steps to correct the problems. ncorporate qualitative variables into the regression model by using dummy variables. Multiple Regression Assumptions The errors are normally distributed The mean of the errors is zero Errors have a constant variance The model errors are independent Model Specification Decide what you want to do and select the dependent variable Determine the potential independent variables for your model Gather sample data (observations) for all variables The Correlation Matrix Correlation between the dependent variable and selected independent variables can be found using Excel:Tools / Data Analysis†¦ / Correlation Can check for statistical significance of correlation with a t test Example A distributor of frozen desert pies wants to evaluate factors thought to influence demand Dependent variable: Pie sales (units per week) Independent variables: Price (in $) Advertising ($100’s) Data is collected for 15 weeks Pie Sales Model Sales = b0 + b1 (Price) + b2 (Advertising) Interpretation of Estimated Coefficients Slope (bi) Estimates that the average value of y changes by bi units for each 1 unit increase in Xi holding all other variables constantExample: if b1 = -20, then sales (y) is expected to decrease by an estimated 20 pies per week for each $1 increase in selling price (x1), net of the effects of changes due to advertising (x2) y-intercept (b0) The estimated average value of y when all xi = 0 (assuming all xi = 0 is within the range of obser ved values) Pie Sales Correlation Matrix Price vs. Sales : r = -0. 44327 There is a negative association between price and sales Advertising vs. Sales : r = 0. 55632 There is a positive association between advertising and sales Scatter DiagramsComputer software is generally used to generate the coefficients and measures of goodness of fit for multiple regression Excel: Tools / Data Analysis†¦ / Regression Multiple Regression Output The Multiple Regression Equation Using The Model to Make Predictions Input values Multiple Coefficient of Determination Reports the proportion of total variation in y explained by all x variables taken together Multiple Coefficient of Determination Adjusted R2 R2 never decreases when a new x variable is added to the model This can be a disadvantage when comparing modelsWhat is the net effect of adding a new variable? We lose a degree of freedom when a new x variable is added Did the new x variable add enough explanatory power to offset the loss of on e degree of freedom? Shows the proportion of variation in y explained by all x variables adjusted for the number of x variables used (where n = sample size, k = number of independent variables) Penalize excessive use of unimportant independent variables Smaller than R2 Useful in comparing among models Multiple Coefficient of Determination Is the Model Significant? F-Test for Overall Significance of the ModelShows if there is a linear relationship between all of the x variables considered together and y Use F test statistic Hypotheses: H0: ? 1 = ? 2 = †¦ = ? k = 0 (no linear relationship) HA: at least one ? i ? 0 (at least one independent variable affects y) F-Test for Overall Significance Test statistic: where F has (numerator) D1 = k and (denominator) D2 = (n – k – 1) degrees of freedom H0: ? 1 = ? 2 = 0 HA: ? 1 and ? 2 not both zero ( = . 05 df1= 2 df2 = 12 Are Individual Variables Significant? Use t-tests of individual variable slopes Shows if there is a linear relationship between the variable xi and yHypotheses: H0: ? i = 0 (no linear relationship) HA: ? i ? 0 (linear relationship does exist between xi and y) H0: ? i = 0 (no linear relationship) HA: ? i ? 0 (linear relationship does exist between xi and y) t Test Statistic: (df = n – k – 1) Inferences about the Slope: t Test Example H0: ? i = 0 HA: ? i ? 0 Confidence Interval Estimate for the Slope Standard Deviation of the Regression Model The estimate of the standard deviation of the regression model is: Standard Deviation of the Regression Model The standard deviation of the regression model is 47. 46 A rough prediction range for pie sales in a given week isPie sales in the sample were in the 300 to 500 per week range, so this range is probably too large to be acceptable. The analyst may want to look for additional variables that can explain more of the variation in weekly sales OUTLIERS If an observation exceeds UP=Q3+1. 5*IQR or if an observation is smaller than LO=Q1 -1. 5*IQR where Q1 and Q3 are quartiles and IQR=Q3-Q1 What to do if there are outliers? Sometimes it is appropriate to delete the entire observation containing the oulier. This will generally increase the R2 and F test statistic values Multicollinearity Multicollinearity: High correlation exists between two independent variablesThis means the two variables contribute redundant information to the multiple regression model Including two highly correlated independent variables can adversely affect the regression results No new information provided Can lead to unstable coefficients (large standard error and low t-values) Coefficient signs may not match prior expectations Some Indications of Severe Multicollinearity Incorrect signs on the coefficients Large change in the value of a previous coefficient when a new variable is added to the model A previously significant variable becomes insignificant when a new independent variable is addedThe estimate of the standard deviation of the mode l increases when a variable is added to the model Output for the pie sales example: Since there are only two explanatory variables, only one VIF is reported VIF is < 5 There is no evidence of collinearity between Price and Advertising Qualitative (Dummy) Variables Categorical explanatory variable (dummy variable) with two or more levels: yes or no, on or off, male or female coded as 0 or 1 Regression intercepts are different if the variable is significant Assumes equal slopes for other variables The number of dummy variables needed is (number of levels – 1)Dummy-Variable Model Example (with 2 Levels) Interpretation of the Dummy Variable Coefficient Dummy-Variable Models (more than 2 Levels) The number of dummy variables is one less than the number of levels Example: y = house price ; x1 = square feet The style of the house is also thought to matter: Style = ranch, split level, condo Dummy-Variable Models (more than 2 Levels) Interpreting the Dummy Variable Coefficients (with 3 Levels) Nonlinear Relationships The relationship between the dependent variable and an independent variable may not be linear Useful when scatter diagram indicates non-linear relationshipExample: Quadratic model The second independent variable is the square of the first variable Polynomial Regression Model where: ?0 = Population regression constant ?i = Population regression coefficient for variable xj : j = 1, 2, †¦k p = Order of the polynomial (i = Model error Linear vs. Nonlinear Fit Quadratic Regression Model Testing for Significance: Quadratic Model Test for Overall Relationship F test statistic = Testing the Quadratic Effect Compare quadratic model with the linear model Hypotheses (No 2nd order polynomial term) (2nd order polynomial term is needed) Higher Order Models Interaction EffectsHypothesizes interaction between pairs of x variables Response to one x variable varies at different levels of another x variable Contains two-way cross product terms Effect of Interacti on Without interaction term, effect of x1 on y is measured by ? 1 With interaction term, effect of x1 on y is measured by ? 1 + ? 3 x2 Effect changes as x2 increases Interaction Example Hypothesize interaction between pairs of independent variables Hypotheses: H0: ? 3 = 0 (no interaction between x1 and x2) HA: ? 3 ? 0 (x1 interacts with x2) Model Building Goal is to develop a model with the best set of independent variablesEasier to interpret if unimportant variables are removed Lower probability of collinearity Stepwise regression procedure Provide evaluation of alternative models as variables are added Best-subset approach Try all combinations and select the best using the highest adjusted R2 and lowest s? Idea: develop the least squares regression equation in steps, either through forward selection, backward elimination, or through standard stepwise regression The coefficient of partial determination is the measure of the marginal contribution of each independent variable, given that other independent variables are in the modelBest Subsets Regression Idea: estimate all possible regression equations using all possible combinations of independent variables Choose the best fit by looking for the highest adjusted R2 and lowest standard error s? Aptness of the Model Diagnostic checks on the model include verifying the assumptions of multiple regression: Each xi is linearly related to y Errors have constant variance Errors are independent Error are normally distributed Residual Analysis The Normality Assumption Errors are assumed to be normally distributed Standardized residuals can be calculated by computerExamine a histogram or a normal probability plot of the standardized residuals to check for normality Chapter Summary Developed the multiple regression model Tested the significance of the multiple regression model Developed adjusted R2 Tested individual regression coefficients Used dummy variables Examined interaction in a multiple regression model Described nonlinear regression models Described multicollinearity Discussed model building Stepwise regression Best subsets regression Examined residual plots to check model assumptions

How Donald Trump Won - The 2016 Presidential Race

Voters and political scientists will debate how Donald Trump won the presidential election in 2016. The businessman and political novice stunned the world by winning a presidential election most analysts and voters believed had firmly been in the hands of Hillary Clinton, who had far more experience in government and had run a more orthodox campaign.   Trump ran his campaign in the most unconventional of ways, insulting large swaths of potential  voters and shunning  the traditional support from his own political party. Trump won at least 290 electoral votes, 20 more than the 270 needed to become president, but got more than 1 million fewer actual votes than Clinton did,  reigniting the  debate over whether the U.S. should scrap the Electoral College. Trump became only the fifth president to be elected without winning the popular vote. The others were Republicans  George W. Bush in 2000,  Benjamin Harrison in 1888 and Rutherford B. Hayes in 1876, and Federalist John Quincy Adams in 1824. So how did Donald Trump win the presidential election by insulting voters, women, minorities, and without raising money or relying on support from the Republican Party? Here are 10 explanations for how Trump won the 2016 election. Celebrity and Success Trump portrayed himself through the 2016 campaign as a successful real-estate developer who created tens of thousands of jobs.  I’ve created tens of thousands of jobs and a great company, said during one debate. In a separate speech, Trump proclaimed his presidency would create job growth like you’ve never seen. I’m very good for jobs .In fact, I will be the greatest president for jobs that God ever created. Trump  runs dozens of companies and serves of numerous corporate boards, according to a personal financial disclosure he filed with the U.S. Office of Government Ethics when he ran for president.  He has said he is worth as much as $10 billion, and though critics suggested he is worth much less Trump projected an image of success and was one of the most well known brands in the county. It also didnt hurt that he was host and producer of NBC’s hit reality series  The Apprentice. High Turnout Among Working-Class White Voters This is the big story of the 2016 election. Working class white voters—men and women alike—fled the Democratic Party and sided with Trump because of his promise to renegotiate trade deals with countries including China and levy stiff tariffs on goods imported from these countries. Trumps position on trade was seen as a way to stop companies from shipping jobs overseas, though many economists pointed out taxing imports would drive up costs to American consumers first. His message resonated with white working-class voters, especially those who live in former steel and manufacturing towns. Skilled craftsmen and tradespeople and factory workers have seen the jobs they loved shipped thousands of miles away, Trump said at a rally near Pittsburgh, Pennsylvania. Immigration Trump promised to essentially lock down the borders to prevent terrorists coming in, an appeal to white voters who were not necessarily worried about crimes being committed by undocumented immigrants by jobs being filled by them. What we are going to do is get the people that are criminal and have criminal records, gang members, drug dealers. We have a lot of these people, probably two million, it could be even three million, we are getting them out of our country or we are going to incarcerate, Trump said. Trumps position contrasted starkly with Clintons position on illegal immigration. James Comey and the FBIs October Surprise A scandal over Clintons  use of a personal email server  as secretary of State had dogged her through early parts of the campaign. But the controversy appeared to be behind her in the waning days of the 2016 election. Most national polls in October and the first days of November showed Clinton leading Trump in the popular vote count; battleground-state polls showed her ahead, too. But 11 days before the election, FBI director James Comey sent a letter to Congress stating he would review emails found on a laptop computer belonging to a Clinton confidant to determined whether they were relevant to the  then-closed investigation of  her use of the personal email server. The letter cast Clintons election prospects into doubt. Then, two days before Election Day, Comey issued a new statement that both confirmed Clinton did nothing illegal but also brought renewed attention to the case. Clinton directly blamed Comey for her loss after the election. Our analysis is that Comey’s letter raising doubts that were groundless, baseless, proven to be, stopped our momentum,† Clinton told donors in a post-election telephone call, according to published reports. Free Media Trump didnt spend a whole lot of money trying to win the election. He didnt have to. His campaign was treated by many major media outlets as a spectacle, as entertainment instead of politics. So Trump got lots and lots of free airtime on cable news and major networks. Analysts estimated Trump had been given $3 billion of free media by the end of the primaries and a total of $5 billion by the end of the presidential election. While free media has long played an important role in our democracy by fostering political discourse and disseminating electoral information, the sheer enormity of coverage on Trump puts a spotlight on how the media may have influenced the course of the election, analysts at mediaQuant wrote in November of 2016.  Free of earned media is the widespread coverage he received by major television networks. He also spent tens of millions of dollars of his own money, mostly fulfilling a vow to finance his own campaign so he could portray himself as being free from ties to special interests.  I dont need anybodys money. Its nice. Im using my own money. Im not using the lobbyists. Im not using donors. I dont care. Im really rich. he said in announcing his campaign in June 2015. Hillary Clintons Condescension  Toward Voters Clinton never did connect to working class voters. Maybe it was her own personal wealth. Maybe it was her status as a political elite. But it most likely had to do with her controversial portrayal of Trump supporters as deplorable. To just be grossly generalistic, you can put half of Trump supporters into what I call the basket of deplorables. Right? Racist, sexist, homophobic, xenophobic, Islamaphobic, you name it,  Clinton said just two months before the election. Clinton apologized for the remark, but the damage was done. Voters who were supporting Donald Trump because they were fearful over their status in the middle class turned solidly against Clinton. Trump running-mate Mike Pence capitalized on Clintons mistake by crystallizing the condescending nature of her remarks.  The truth of the matter is that the men and women who support Donald Trumps campaign are hard-working Americans, farmers, coal miners, teachers, veterans, members of our law enforcement community, members of every class of this country, who know that we can make America great again, Pence said. Voters Didnt Want a Third Term for Obama Regardless of how popular Obama was, its incredibly rare for presidents from the same party to win back-to-back terms in the White House, partly because voters become fatigued by a president and his party by the end of eight years.  In our  two-party system, the last time voters elected a Democrat to the White House after a president from the same party had just served a full term was in 1856, before the Civil War. That was James Buchanan. Bernie Sanders and the Enthusiasm Gap Many—not all, but many— supporters of Vermont Sen. Bernie Sanders did not come around to Clinton after she won the brutal, and what many thought ,  rigged, Democratic primary. In a scathing criticism of liberals Sanders supporters who didnt support Clinton in the general election, Newsweek magazines Kurt Eichenwald wrote:   Awash in false conspiracy theories and petulant immaturity, liberals put Trump in the White House. Trump won slightly fewer votes than Romney did in 2012—60.5 million compared with  60.9 million. On the other hand, almost 5 million Obama voters either stayed home or cast their votes for someone else. More than twice as many millennials—a group heavily invested in the â€Å"Sanders was cheated out of the nomination† fantasy—voted third-party. The laughably unqualified Jill Stein of the Green Party got 1.3 million votes; those voters almost certainly opposed Trump; if just the Stein voters in Michigan had cast their ballot for Clinton, she probably would have won the state. And there is no telling how many disaffected Sanders voters cast their ballot for Trump. Obamacare and Health Care Premiums Elections are always held in November. And November is open-enrollment time. In 2016, as in previous years, Americans were just getting notice that their health insurance premiums were rising dramatically, including those who were purchasing plans on the marketplace set up under President Barack Obamas Affordable Care Act, also known as Obamacare. Clinton supported most aspects of the health care overhaul, and voters blamed her for it. Trump, on the other hand, promised to repeal the program.