Rc Coleman Managerial Report Essay

K 13. C 14. C 15. E 16. D 17.

Jack (45,000 – 500 – 2000 * 25%, yr1/ 134,500 – 1,000 – 2,500 * 25%, yr2)

(1) TIME ALLOWED – 3 Hours (2) TOTAL NUMBER OF QUESTIONS – 6 (3) ANSWER ALL QUESTIONS (4) THE QUESTIONS ARE OF EQUAL VALUE (5) THIS PAPER MAY NOT BE RETAINED BY THE CANDIDATE (6) ONLY CALCULATORS WITH AN AFFIXED “UNSW APPROVED” STICKER MAY BE USED (7) STATISTICAL FORMULAE ARE ATTACHED AT END OF PAPER STATISTICAL TABLES ARE ATTACHED AT END OF

1. Using the sample data given in Table 2-20, make a recommendation for how many units of each style Wally should make during the

Frumherj is a car inspection company in Iceland. They are one of the largest in the country, but they want to continue to grow and to outpace their competitors. However, there are some inefficiencies in their process that must be addressed before they can meet their goals. One of their first problems is maintaining an even flow in their process environment. Due to the nature of the inspections and the cold weather in Iceland, they are much more busy in the summer that they are in the winter. This makes it difficult to keep the right amount of employees. There is little they can do to avoid this problem, but rather they should examine their historical data to determine how many employees they will need in order to meet expected

Complete exercises 12.1, 12.4, 12.9, 12.17, 12.21, 12.43 (assume “Calories” is the “x” variable and “Fat” is the “y” variable). You will need:

Year |# of Lots Sold |Ave. Lot Price |Gross Annual Cash Flows |Mark. $ Misc. costs |Developer's P&O |Net Annual Cash Flows |Discount Factors |PV of Cash Flows | |0 |0 | |0 |0 |0 |0 |1 |0 | |1 |10 |50000 |500000 |25000 |25000 |450000 |0.9091 |409095 | |2 |10 |50000 |500000 |25000 |25000 |450000 |0.8264 |371880 | |3 |10 |50000 |500000 |25000 |25000 |450000 |0.7513 |338085 | |4 |10 |50000 |500000 |25000 |25000 |450000 |0.683 |307350 | |5 |10 |50000 |500000 |25000 |25000 |450000 |0.6209 |279405 | |6 |10 |50000 |500000 |25000 |25000 |450000 |0.5645 |254025 | |7 |10 |50000 |500000 |25000 |25000 |450000 |0.5132 |230940 | |8 |10 |50000 |500000 |25000 |25000 |450000 |0.4665 |209925 | |9 |10 |50000 |500000 |25000 |25000 |450000 |0.4241 |190845 | |10 |10 |50000 |500000 |25000 |25000 |450000 |0.3855 |173475 | | | | | | | | |Total |2765025 | | | | | | | | |Rounded |2765000 | | | | | | | | |PV per Lot |27650 | |

1. In order to implement an organizations commitment to social responsibility it is necessary to identify what social problem the organization intends to address, develop policies on what the organization plans to do to successfully fulfill its obligation and ensure stakeholder buy-in. The main obstacles an organization faces when implementing socially responsible policies is pressure from stockholders and business analysis who want steady increase in earnings. Without steady increase in profits, it becomes difficult to reinvest money in these areas. The following actions can be taken toward increased social responsibility:

of years in the Company…………31 Table 5 Profile of Respondents According to No. of years as CSA……………………...32 Table 6 Benefits Mean……………………………………………………………………33 Table 7 Relationship with supervisor Mean……………………………………………...33 Table 8 Job Security Mean……………………………………………………………….34 Table 9 Job Satisfaction Mean……………………………………………………………34 Table 10 Regression Result for Job Satisfaction with respect to Benefits, Relationship with Supervisor and Job Security………………………………………………..35 Table 11 ANOVA (Analysis of Variance) for Job Satisfaction with regard to Benefits, Relationship with Supervisor and Job Security………………………………….36 Table 12 Multiple Regression Results with Job satisfaction as dependent variable………36

Next, the task was to see the expected number of breakdowns per year. The information which was useful here was the graph in respect to the likely probability of a breakdown within a six week period of time that was provided by the case study itself. The first step was to input this information into Excel using a chart that plotted the x and y intervals of the 6 week period using the

There needs to be a clear definitive vision on where progress should be in the near future. Because the city of Pleasant Valley is in fact so small, there is only a handful of local businesses that help sustain the city’s population and encourage growth. In fact the city makes most of her revenue off the Police Department’s citations. With an analysis of their interpersonal skills, management strategies, and various management principles I hope to paint a picture of how smaller cities are beginning to show their business savvy to stimulate growth. Through focusing my analysis on the local Police Department I hope to show what methods make them successful at being such a significant source of revenue to such a small town; thus becoming a new entity I like to call “Small Town Inc.” while illustrating what kind of impact they pose on their community.

The goal of open-book management is to get every employee thinking and acting like a business owner.

I then recorded down my results working out an average and efficiency; put this data into a table and a graph. Before reaching my conclusion.

List of calculations made, (All the calculations are made in excel and is attached also the value of Median, Q1 and Q3 from the ogive graph generated from excel.

For this analysis I have selected the variables “APPOINTMENTS”, “OUTBOUND” and “MINUTES” as the 1st, 2nd, and 3rd individual variables respectively. Also the 1st, 2nd, and 3rd pairs of variables I have selected for this analysis are respectively “APPOINTMENTS and OUTBOUND”, “APPOINTMENTS and MINUTES” and “MINUTES and OUTBOUND”. PART A: Exploratory Data Analysis 1. Graphical and numerical summaries for 1st individual variable, i.e. APPOINTMENTS. Descriptive Statistics: APPOINTMENTS Variable N Mean StDev Minimum Median Maximum Skewness Kurtosis APPOINTMENTS 100 28.780 4.378 19.000 29.000 39.000 0.04 -0.16 The shape of the histogram for the variable “APPOINTMENTS” depicts that the distribution of that variable is approximately normal with (M = 28.78, SD = 4.378). The median (29.00) which is almost coincides with the mean (28.78) and the coefficient of skewness (.04) is almost same as ‘0’, also confirms that the distribution is symmetric. The coefficient of kurtosis (–.16), close to ‘0’ specifies that the distribution of “APPOINTMENTS” is approximately normal. 2. Graphical and numerical summaries for 2nd individual variable, i.e. OUTBOUND. Descriptive Statistics: OUTBOUND Variable N Mean StDev Minimum Median Maximum Skewness Kurtosis OUTBOUND 100 96.63 18.33 61.00 95.50 138.00 0.04 -0.67 The shape of the histogram for the variable “OUTBOUND” depicts that the distribution of that variable is approximately normal with (M = 96.63, SD = 18.33). The median (95.50) which is almost