Reference no: EM132251103
Assignment Problems: Statistics for managers
Note - Solve the problems using Microsoft Excel 8th Edition, Levine, Stephen & Szabat and PHsat.
Problem 1 - All parts, post and explain ANOVA table
Zagat's publishes restaurant ratings for various locations in the United States. The file Restaurants contains the Zagat rating for food, decor, service, and the cost per person for a sample of 100 restaurants located in the center of New York City and in an outlying area of New York City. Develop a regression model to the predict the cost per person, based on a variable that represents the sum of the ratings for food, decor, and service.
Sources: Extracted from Zagat Survey 2015, New York City.
a. Construct a scatter plot.
b. Assuming a linear relationship, use the least-squares method to compute the regression coefficients b0 and b1.
c. Interpret the meaning of the Y intercept, b0, and the slope, b1, in this problem.
d. Predict the mean cost per person for a restaurant with a stimulated rating of 50.
e. What should you tell the owner of a group of restaurants in this geographical area about the relationship between the summated eating and the cost of a meal?
Problem 2 - Part a, b, d, post and explain ANOVA table
The production of wine is a multibillion-dollar worldwide industry. In an attempt to develop a model of wine quality as judged by wine experts, data was collected from red wine variants of Portuguese "Vinho Verde" wine. A sample of 50 wines is stored in VinhoVerde. (Data extracted from P. Cortez, Cerdeira, A., Almeida, F., Matos, T., and Reis, J., "Modeling Wine Preferences by Data Mining from Physiochemical Properties," Decision Support Systems, 47, 2009, pp. 547-553) Develop a multiple linear regression model to predict wine quality, measured on a scale from 0 (very bad) to 10 (excellent) based on alcohol content (%) and the amount of chlorides.
a. State the multiple regression equation.
b. Interpret the meaning of the slopes, b1 and b2, in this problem.
c. Explain why the regression coefficient, b0, has no practical meaning in the context of this problem.
d. Predict the mean wine quality rating for wines that have 10% alcohol and chlorides of 0.08.
e. Construct a 95% confidence interval estimate for the mean wine quality rating for wines that have 10% alcohol and chlorides of 0.08.
f. Construct a 95% prediction interval for the wine quality rating for an individual wine that has 10% alcohol and chlorides of 0.08.
g. What conclusions can you reach concerning this regression model?
Problem 3 - Part a, b
In the production of printed circuit boards, errors in the alignment of electrical connections are a source of scrap. The data in the file RegistrationError-HighCost contains the registration error and the temperature used in the production of circuit boards in an experiment in which higher cost material was used. (Data extracted from C. Nachtsheim and B. Jones, "A Powerful Analytical Tool," Six Sigma Forum Magazine, August 2003, pp. 30-33.)
a. Construct a scatter plot for temperature and registration error.
b. Fit a quadratic regression model to predict registration error and state the quadratic regression equation.
c. Perform a residual analysis on the results and determine whether the regression model is valid.
d. At the 0.05 level of significance, is there a significant quadratic relationship between temperature and registration error?
e. At the 0.05 level of significance, determine whether the quadratic model is a better fit than the linear model.
f. Interpret the meaning of the coefficient of multiple determinations.
g. Compute the adjusted r2.
h. What conclusions can you reach concerning the relationship between registration error and temperature?
Problem 4 -
Use Modified Moving Average worksheet; see attached Excel Spreadsheet.
The following data, stored in CoreAppliances provide the total number of shipments of core major household appliances in the U.S. from 2000 to 2014 (in millions).
|
Year
|
Shipments
|
Year
|
Shipments
|
|
2000
|
38.4
|
2008
|
39.8
|
|
2001
|
38.2
|
2009
|
36.5
|
|
2002
|
40.8
|
2010
|
38.2
|
|
2003
|
42.5
|
2011
|
36.0
|
|
2004
|
46.1
|
2012
|
35.8
|
|
2005
|
47.0
|
2013
|
39.2
|
|
2006
|
46.7
|
2014
|
41.5
|
|
2007
|
44.1
|
|
|
a. Plot the time series.
b. Fit a three-year moving average to the data and plot the results.
c. Using a smoothing coefficient of W = 0.50, exponentially smooth the series and plot the results.
d. What is your exponentially smoothed forecast for 2015?
e. Repeat (c) and (d), using W = 0.25.
f. Compare the results of (d) and (e).
g. What conclusions can you reach concerning the total number of shipments of core major household appliances in the U.S. from 2000 to 2014 (in millions)?
Statistics Data Analysis Project requirements -
Research title---determine whether or not Schools with music programs, secondary education level, have estimated higher graduation and attendance rates from participation compared to schools without music education and possible relationships with selected variables (race/ethnicity, religion, gender, musical instrument and region).: Collate Data from 2000 to 2015
1) Format Power Point 10 Slide template provided. Note-three slides already done need the main research done and data provided on slides as indicated below.
2) Use reputable sources for info such as Data.gov, National Institute of Health, google scholar, etc....
3) Data slides should include have tables, graphs or charts followed by a descriptive data summary slide, summarize data slide and Regression Analysis slide with results
4) Conclusion slide tied to original hypothesis or research question.
Note: additional info- use Statistics language p-value, confidence Interval (CI), standard deviation (SD), error, skewness, ANOVA, etc....
Slide 1: done
Slide 2: Narrative provided on left of slide but would like the expert to place picture of a Violin to right of narrative.
Slide 3: done
Slide 4: complete narrative on left with data researched by the expert and to the right of narrative provide a provide table, chart or graph showing the relationship of music participation by year against selected variables and graduation.
Slide 5: Descriptive summary: provide stat table with data from research findings. See template provided.
Slide 6: Add graph for data provided on slide 5 or appropriate graphics
Slide 7: Regression Analysis see example provided on slide template and provide similar with research data for topic
Slide 8: Conclusion follow template example provided an provide narrative based on expert research of topic and provide small data summary to reflect as shown by example.
Slide 9: Partially done---just place word Question? (with question mark) on page alone.
Slide 10: Reference slide; at least two references
Slide 11: foot note/explanation slide of any data in statistical language for slides 4, 5, 6 and 7.
Attachment:- Assignment Files.rar