Purpose of Assignment The purpose of this assignment is to develop students' analytical capabilities to evaluate, analyze, and apply descriptive statistics techniques to real-world datasets. Assignment Steps Resources: Microsoft Excel®, Case Study: MBA Schools in Asia-Pacific Review the Case Study: MBA Schools in Asia-Pacific and the Case Study: MBA Schools in Asia-Pacific data set. Prepare a 1,050-word managerial report for your boss.Use the following questions for guidelines and directions on what to include in the report:What is the type of data (Quantitative or Qualitative) for each of the columns (variables) in the dataset? If quantitative, is the data discrete or continuous? Neatly summarize your response in a table for all the columns (variables).Using Excel®, find the mean, median, standard deviation, minimum, maximum, and the three quartiles for each of the quantitative variables identified in part 1 above. Neatly summarize in a table on this document. Comment on what you observe.What are the minimum and maximum full-time enrollments? Which schools have the minimum and maximum full-time enrollments?What is the average number of students per faculty member? Is this low or high? What does this mean to prospective applicants who are interested in pursuing an MBA in one of the leading international business schools?What are the mean, median, and modal ages? What does this mean to prospective applicants?What is the mean percentage of foreign students? How many and which schools have 1% and 0% foreign students? Which schools have highest percentage of foreign students? Please state these percentages.What percentage of schools require the GMAT test?What percentage of schools require English tests such as Test of English as a Foreign Language (TOEFL)?What percentage of schools require work experience? From this percentage, does this appear to be a significant factor in gaining admissions?What are the mean and median starting salaries? Which schools have the minimum and maximum starting salaries? How much are these minimum and maximum salaries?What are the mean tuition for foreign students and for local students? Does there appear to be a significant difference? What is the difference between the two means?How many schools require work experience and how many of them don't? What is the mean starting salary for schools requiring work experience? What is the mean starting salary for schools requiring no work experience?How many schools require English tests and how many don't? What is the mean starting salary for schools requiring English tests? What is the mean starting salary for schools requiring no English tests?Comment on the skewness for the data on starting salaries:Plot a histogram and determine the skewness.Find the skewness coefficient.Find the mean, median, and mode for starting salaries and compare the three measures to determine skewness.Finally, use Empirical Rule on the starting salaries and determine whether the salaries follow the Empirical Rule.Format your assignment consistent with APA format.

Required ResourcesRead/review the following resources for this activity:Textbook: Chapter 4 (All Sections)LessonMinimum of 1 scholarly sourceInitial Post InstructionsTopic: Poisson Probability DistributionThe Poisson Distribution is a discrete probability distribution where the number of occurrences in one interval (time or area) is independent of the number of occurrences in other intervals.April Showers bring May Flowers!! Research the "Average Amount of Days of Precipitation in April" for a city of your choice.In your initial post,IntroduceIntroduce the City and State. Let us know a fun fact!Tell us the average number of days of precipitation in that city for the month of April.Cite your SourceCalculationsWhat is the probability of having exactly 10 days of precipitation in the month of April?What is the probability of having less than three days of precipitation in the month of April?What is the probability of having more than 15 days of precipitation in the month of April?AnalysisWrite a sentence for each of the probabilities explaining what those probabilities mean in context of days of precipitation in your chosen city.Would any of the situations be considered unusual? Why or Why Not?

For this assignment you will implement a project involving linear curve-fitting and interpretation. You will assess the appropriateness of a linear model, and explore the predictive power of the model. You will use appropriate technology to perform the modeling tasks.For this assignment, collect data exhibiting a relatively linear trend, find the line of best fit, plot the data and the line, interpret the slope, and use the linear equation to make a prediction. Also, find r2 (coefficient of determination) and r (correlation coefficient). Discuss your findings. Your topic may be that is related to sports, your work, a hobby, or something you find interesting. If you choose, you may use the suggestions described below. A Linear Model Example and Technology Tips are provided in separate documents.Tasks for Linear Regression Model (LR)(LR-1) Describe your topic, provide your data, and cite your source. Collect at least 8 data points. Label appropriately. (Highly recommended: Post this information in the Linear Model Project discussion as well as in your completed project. Include a brief informative description in the title of your posting. Each student must use different data.) The idea with the discussion posting is two-fold: (1) To share your interesting project idea with your classmates, and (2) To give me a chance to give you a brief thumbs-up or thumbs-down about your proposed topic and data. Sometimes students get off on the wrong foot or misunderstand the intent of the project, and your posting provides an opportunity for some feedback. Remark: Students may choose similar topics, but must have different data sets. For example, several students may be interested in a particular Olympic sport, and that is fine, but they must collect different data, perhaps from different events or different gender.(LR-2) Plot the points (x, y) to obtain a scatterplot. Use an appropriate scale on the horizontal and vertical axes and be sure to label carefully. Visually judge whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different topic or data set.)(LR-3) Find the line of best fit (regression line) and graph it on the scatterplot. State the equation of the line.(LR-4) State the slope of the line of best fit. Carefully interpret the meaning of the slope in a sentence or two.(LR-5) Find and state the value of r2, the coefficient of determination, and r, the correlation coefficient. Discuss your findings in a few sentences. Is r positive or negative? Why? Is a line a good curve to fit to this data? Why or why not? Is the linear relationship very strong, moderately strong, weak, or nonexistent?(LR-6) Choose a value of interest and use the line of best fit to make an estimate or prediction. Show calculation work.(LR-7) Write a brief narrative of a paragraph or two. Summarize your findings and be sure to mention any aspect of the linear model project (topic, data, scatterplot, line, r, or estimate, etc.) that you found particularly important or interesting. You may submit all of your project in one document or a combination of documents, which may consist of word processing documents or spreadsheets or scanned handwritten work, provided it is clearly labeled where each task can be found. Be sure to include your name. Projects are graded on the basis of completeness, correctness, ease in locating all of the checklist items, and strength of the narrative portions.Here are some possible topics: Choose an Olympic sport -- an event that interests you. Go to http://www.databaseolympics.com/ and collect data for winners in the event for at least 8 Olympic games (dating back to at least 1980). (Example: Winning times in Men's 400 m dash). Make a quick plot for yourself to "eyeball" whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different event.) After you find the line of best fit, use your line to make a prediction for the next Olympics (2014 for a winter event, 2016 for a summer event ).Choose a particular type of food. (Examples: Fish sandwich at fast-food chains, cheese pizza, breakfast cereal) For at least 8 brands, look up the fat content and the associated calorie total per serving. Make a quick plot for yourself to "eyeball" whether the data exhibit a relatively linear trend. (If so, proceed. If not, try a different type of food.) After you find the line of best fit, use your line to make a prediction corresponding to a fat amount not occurring in your data set.) Alternative: Look up carbohydrate content and associated calorie total per serving.Choose a sport that particularly interests you and find two variables that may exhibit a linear relationship. For instance, for each team for a particular season in baseball, find the total runs scored and the number of wins. Excellent websites: http://www.databasesports.com/ and http://www.baseball-reference.com/