Analyzing Data Using Pivot Tables – An Example Remember assignment 5 where you were asked to compare Invoice amounts to Sales Order amounts? You had to create a query to join together 2 tables from an Access database. If the results of that query had been downloaded into an Excel file (a simple thing to do)‚ you could have used the Excel file and a Pivot table to help in the analysis. Before you try to follow this example‚ you should learn as much as you can about Pivot Tables from Microsoft’s
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a. Name of dataset Data Set 14: Coin Weights (grams) b. What does each observation (row) in the dataset represent? Each observation (row) represents what type of coin was used and pre/post years. Here we have the Indian pennies‚wheat pennies‚ pre 1983‚post 1983‚ Canadian pennies‚pre 1964 quarters‚ post 1964 quarters‚ and dollar coins. c. Give the name of one qualitative variable and one quantitative variable from the data set. Note: Your dataset may not have both types (if it does not‚ please
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system. True (Seven steps in the forecasting system‚ moderate) 6. The sales force composite forecasting method relies on salespersons’ estimates of expected sales. True (Forecasting approaches‚ easy) 7. A time-series model uses a series of past data points to make the forecast. True (Forecasting approaches‚ moderate) 8. The quarterly "make meeting" of Lexus dealers is an example of a sales force composite forecast. True (Forecasting approaches‚ easy) 9. Cycles and random variations are
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Analysis of Data The researcher distributed 150 questionnaires to people and students from different schools. After collecting the papers‚ each was tallied one by one. The questionnaire has a total of Seven(7) questions each with a different set and amount of answers. One hundred(100) questionnaires were distributed in person while the Fifty(50) were answered online. The results of the survey will be explained by percentage and shown through pie chart as well along with a slight conclusion for
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Known as America’s pastime‚ baseball is a game in which generations of children of all ages grow up playing in parks‚ streets‚ and alleyways throughout America. These same children grew up idolizing names such as Cy Young‚ Babe Ruth‚ Mickey Mantle‚ Jackie Robinson‚ and Hank Aaron. These men‚ as thousands of men before and after them‚ played in a league simply named Major League Baseball. Major League Baseball is rich in history with statistics and records dating back to 1873. Baseballchronology.com
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Business Management Masters of Business Administration Regression Project Estimating Stock Prices of Independent E&P Companies Assignment for Course: HR 533‚ Applied Managerial Statistics Submitted to: Professor Mohamed Nayebpour Submitted by: Leah A. O’Daniels Location of Course: Blended – Houston Campus & On-line Date of Submission: December 16‚ 2011 Regression Analysis: StockPrice versus Sales(B) The regression equation is StockPrice = 15.64 + 4.441 Sales(B) S = 11
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c. ratio scale d. interval scale 2. Data obtained from a nominal scale a. must be alphabetic b. can be either numeric or nonnumeric c. must be numeric d. must rank order the data 3. In a post office‚ the mailboxes are numbered from 1 to 4‚500. These numbers represent a. qualitative data b. quantitative data c. either qualitative or quantitative data d. since the numbers are sequential‚ the data is quantitative 4. A tabular summary of a set of data showing the fraction of the total number
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Linear Regression & Best Line Analysis Linear regression is used to make predictions about a single value. Linear regression involves discovering the equation for a line that most nearly fits the given data. That linear equation is then used to predict values for the data. A popular method of using the Linear Regression is to construct Linear Regression Channel lines. Developed by Gilbert Raff‚ the channel is constructed by plotting two parallel‚ middle lines above and below a Linear Regression
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Topic 8: Multiple Regression Answer a. Scatterplot 120 Game Attendance 100 80 60 40 20 0 0 5‚000 10‚000 15‚000 20‚000 25‚000 Team Win/Loss % There appears to be a positive linear relationship between team win/loss percentage and game attendance. There appears to be a positive linear relationship between opponent win/loss percentage and game attendance. There appears to be a positive linear relationship between games played and game attendance. There does not appear to be any relationship
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Cox Regression Models Questions with Answers Worked Example An investigation is carried out into popularity of new cars being bought in the showroom of a Mercedes dealer. Data recorded for each car included colour‚ engine size and car type. A Cox proportional hazards model was fitted to the data and the results are given below: Write down the Cox hazard function according to this model. With regards to the model you have written down above state the following: • To which class of car does the
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