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PATRICIA FULLER 10/31/2010 11:52 AM [Hide comments] Rounding error in p(orange)s/b .2162 (-1 point) Rounding precision in Sample mean (4-6 Rounding error in p(orange)s/b .2162 (-1 point) Rounding precision in Sample mean (4-6 Decimal De … places) (-1 point) Error in Sample Standard Deviation s/b 1.9708 (-1 pt) Written Description of Histogram (-1 point) PATRICIA FULLER 10/29/2010 8:08 PM [Hide comments] Rounding error in p(orange)s/b .2162 (-1 point) Rounding precision in Sample mean (4-6 Rounding error in p(orange)s/b .2162 (-1 point) Rounding precision in Sample mean (4-6 Decimal D… places) (-1 point) Error in Sample Standard Deviation s/b 1.9708 (-1 pt) Written Description of Histogram (-1 point) VANESSA HENDERSON-ROLLE 10/24/2010 9:34 PM [Hide comments] Good Evening Professor, Please find the attached M&M Project Part II for your review. … Good Evening Professor, Please find the attached M&M Project Part II for your review. Thank You! * Times are displayed in (GMT-07:00) Mountain Time (US & Canada) PATRICIA FULLER 11/17/2010 9:26 PM [Hide comments] It looks like you copied the Green results for the Orange line (-3) What is #7? The Confidence interval It looks like you copied the Green results for the Orange line (-3) What is #7? The Confid … pasted from StatCrunch is correct for the C.I. of the mean. Your bonus is incorrect. Use the formula from page 338 in the text. PATRICIA FULLER 11/17/2010 9:01 PM [Hide comments] It looks like you copied the It looks like you copied the Green results for the Orange line (-3) What is #7? The Conf … Green results for the Orange line (-3) What is #7? The Confidence interval pasted from StatCrunch is correct for the C.I. of the mean. Your bonus is incorrect. Use the formula from page 338 in the text. VANESSA HENDERSON-ROLLE 11/14/2010 7:18 PM [Hide comments] Hello Professor, Please find the attached Hello Professor, Please find the attached M&M Project Part 3, with an attempt to complete M&M … Project Part 3, with an attempt to complete the bonus question. Thanks! * Times are displayed in (GMT-07:00) Mountain Time (US & Canada) PATRICIA FULLER 12/1/2010 10:00 PM [Hide comments] Everything is great, except for the conclusion. You Everything is great, except for the conclusion. You should bring in a short statement of should bring in what … a short statement of what that means in relationship to the scenario (- .5 point) VANESSA HENDERSON-ROLLE 11/28/2010 5:40 PM Hello Professor, Please find the attached M&M Project for PATRICIA FULLER 12/20/2010 6:43 PM [Hide comments] I agree, it was difficult to narrow down - no student submitted a paper of only 3 pages (including yours, which was 5 pages). I don't understand what you mean by your analysis of I agree, it was difficult to narrow down - no student submitted a paper of only 3 standard pages (including y … deviation. I do not find any explanations of the terminology, nor did I find any explanation of a way to investigate the unexpected results. If you would like to revise and resubmit, I will regrade this project. PATRICIA FULLER 12/18/2010 1:54 PM [Hide comments] I agree, it was difficult to narrow down - no student submitted a paper of only 3 pages (including yours, which was 5 pages). I don't I agree, it was difficult to narrow down - no student submitted a paper of only 3 understand what pages (including y … you mean by your analysis of standard deviation. I do not find any explanations of the terminology, nor did I find any explanation of a way to investigate the unexpected results. If you would like to revise and resubmit, I will regrade this project. VANESSA HENDERSON-ROLLE 12/16/2010 6:21 AM [Hide comments] Professor thanks for your feedback. This was a difficult report to narrow now and articulate in 3 pages. I actually cut out a lot to show the analysis, however I did indicate the rationale as to what I believed to be my analysis for the standard deviation. store Professor thanks for your feedback. This was a difficult report to narrow now and locations, articulate i … unknown factors based on students testing methods and validity and production which were not monitored or controlled as a part of this study. (paragraph 1) Please advise and consider these components in your final grading. I will check back today. Thanks for your consideration. PATRICIA FULLER 12/15/2010 7:15 PM [Hide comments] 1. Present the methods, analysis and 1. Present the methods, analysis and results for the … results for the five parts of the project. (30 points) 2. Explain how to investigate unexpected results (failed tests in Part 4) and speculate on at least three plausible causes for the observed results You did not suggest any possible causes for the unexpected results. (0 points) 3. Clarity: Explain all statistical terminology in every-day language. You did not attempt to define any of the terminology in every day language. (0 points) 4. Writing : Grammar, sentence structure, paragraph structure, spelling, punctuation, APA usage. (30 points) VANESSA HENDERSON-ROLLE 12/5/2010 9:07 PM [Hide comments] Good Day Professor, Please find the attached M&M Project Report attached for your review.& … Good Day Professor, Please find the attached M&M Project Report attached for your review. Thank You. * Times are displayed in (GMT-07:00) Mountain Time (US & Canada) MAT 300 m&ms® Project Part 1 (10 pts) Throughout this course we will be using m&ms® data to help explain some of the concepts being taught as well as give you a feel for how these methods can be used. We will be exploring plain m&ms® and I have chosen to use the 1.69 oz size bags for convenience and affordability. From a larger perspective, the purpose of our report is to examine the packaging process for plain 1.69 ounce bags of m&ms®. In order to get started, everyone needs to visit three (3) different stores and purchase a plain m&ms® 1.69 oz bag of candy. It is not necessary to keep track of which bag came from which store. Why do we need to do this? We are taking a sample of the population of all 1.69 oz bags of plain m&ms® that are produced. In order for our results to be meaningful, we need a random sample. Random samples are found by sampling at complete and total random. By visiting three different stores and then randomly selecting a bag from the display, we are assuring that we are obtaining a true random sample. Other sampling methods will also produce a random sample. The concepts of population, sample, and sampling methods will be explained further in Chapter 1. Download the mnminput.xls file found in doc sharing. Once you have your three bags, you will need to open each one individually and record the number of candies of each color within the bag (blue, orange, green, yellow, red, and brown) into the file. Once you have done this for each bag, save the file and place it into the Part 1 dropbox in eCollege. Here is the best part of the project. When you are done counting the colors and recording your data, feel free to enjoy the candy! Please note that everyone’s data will be combined into ONE class data set. This data set will be used for all the remaining parts of the project. There will be an announcement when the class data set has been uploaded to Doc Sharing. Because we are only sampling 1.69 oz bags, all our conclusions will be based upon plain 1.69 oz bags of m&ms®. We will be focusing on the overall percentage of each color and the total number of candies per bag. At the end of the project, you will be writing a summary of all parts of the project. It will be written as a formal report to a supervisor or manager. More information will be given. MAT 300 M&Ms® Project Part 2 (30 pts) Use the Excel data file found in the doc sharing area (mnmproject.xls) to complete this assignment. If using Excel 2003, you will want to go to Tools > Add-Ins and make sure the boxes to the left of both analysis toolpaks are checked as we will be using those tools throughout the term. If using Excel 2007, you will click on the Microsoft Office Button in the upper left, then click “Excel Options”. Click on Add-Ins, then in the Manage box, select Excel Add-Ins. Click Go. In the “Add-Ins available box, select the Analysis ToolPak check box and then “Ok”. Please refer to the sample project file (samplemnmpart2.xls) in the Doc Sharing area for an example of what your completed file will look like if you follow all the outlined steps. Be sure to submit your Excel file into the dropbox. From this point forward, we will be focusing on the data from two perspectives: color proportions and the number of candies per bag. For the color proportions, the information that will be used is the total for each color and the total number of candies sampled. For the number of candies per bag, you will use the data in the num. candies in bag column. 18 pts (3 for each color). Add up each of the columns. Calculate the sample proportions ( ) for each of the colors. For example, the sample proportion of blue candies would be the total number of blue candies from all the bags divided by the total number of candies in all the bags. 3 pts. Calculate the sample mean ( ) number of candies per 1.69 oz bag. (Find the mean of the number of candies in bag column). 3 pts. In another sheet in the Excel data file, create a histogram for the number of candies per bag. To do this in Excel 2003, go to Tools in the menu and click on Data Analysis, then select Histogram. In Excel 2007, select the Data tab and then click on Data Analysis in the Analysis box. Click in the input range and then select the column containing the total number of candies per bag. Be careful that you do not include the cell that has the total for the column. Select the bin column on the data page for bin range. The “bin” column tells Excel how to group the data into classes for graphing. If you include the cell with the labels (total and bin) when selecting the cells, be sure the box next to Labels is checked. Under output options, select the new worksheet ply and name it Histogram. Check next to Chart output. Finally click ok, and the histogram will be within the new worksheet page. If you will click and hold on the square in the bottom center of the histogram chart, then move the mouse down, you can widen the chart and make it easier to read. If you do not have the Analysis toolpak in Excel, you can use StatCrunch to do this part. A link to StatCrunch can be found under the Tools for Success, the webliography and on each homework and MML quiz problem. Copy the “number of candies in bag” column into StatCrunch. To do this, you will copy the column in Excel including the column header (num. candies in bag). Then after opening StatCrunch, you will select Data > Load Data > from paste. In the window that opens, click on “paste data from clipboard”, then click “okay”. The data will be loaded into StatCrunch. Next select Graphics > Histogram. In the popup window, select the name of the column that contains your data, click next. Next, enter 1 in the box to the right of “binwidth”, then click “Create Graph!” The output can be copied and pasted into your Excel file. 3 pts. In another sheet in the file, use Excel to compute the descriptive statistics for the total number of candies per bag. This data includes sample mean, sample standard deviation, median, mode, as well as other useful information. To complete this, select Data Analysis again, then select Descriptive Statistics. In the input range, select the “number of candies in bag” column. Include the first row containing the label. Make sure the grouped by columns is selected and check the box next to “Labels in first row”. For the output, select new worksheet ply and name it Descriptive Stats. Check the box next to “Summary Statistics”. You can also do this part in StatCrunch. With the “number of candies in bag” data copied in the previous step, select Stat > Summary Stats > Columns. In the popup window, select the name of the column that contains your data, then click “Calculate”. The output can be copied and pasted into your Excel file. 3 pts. Finally, in another worksheet titled “Part 2 Summary”, please summarize the following information from this part of the project: Total number and calculated proportions (sample proportions) for each color Sample mean number of candies per bag Sample standard deviation of mean number of candies per bag Written description of the histogram. Describe its shape: normal, skewed, etc. Also identify any potential outliers. Sample sizes of this project o Total number of candies sampled (total of the number of candies in bag column). This is the sample size for all future parts dealing with color proportions. o Total number of bags sampled (number of rows of data). This is the sample size for all future parts dealing with the mean and standard deviation number of candies per bag. NOTE: You should be using the combined class data set, not your sample of three bags. It is imperative that you correctly complete the Part 2 Summary as we will be using the information summarized on that page for ALL the remaining parts of the project. To help keep the sample sizes straight, remember that when you calculated the proportion of each color, you divided by the total number of candies sampled. When you calculated the mean number candies per bag, you divided by the total number of bags. At the end of this project, you will be writing a report, explaining the method and presenting the results from each part of the project. You might find it useful to write this as you complete the work, so the report will be mostly written by the time it is assigned. MAT 300 M&Ms® Project Part 3 (21 pts) We will be constructing confidence intervals for the proportion of each color as well as the mean number of candies per bag. You will use the methods of 6.3 for the proportions and 6.1 for the mean. For the Bonus, you will use the sample size formula on page 338. You can use StatCrunch to assist with the calculations. A link for StatCrunch can be found under Tools for Success in Course Home. Here is also a link: http://statcrunch.pearsoncmg.com/statcrunch/larson_les4e/dataset/index.html. You can also find additional help on both confidence intervals and StatCrunch in the Online Math Workshop under Tab: “MAT300 Archived Workshops”. Specifically you will be looking for Confidence Intervals and Using Technology – CI. Submit your answers in Excel, Word or pdf format. Upload your file to the dropbox. If calculating by hand, be sure to keep at least 4-6 decimal places for the sample proportions to eliminate large rounding errors. 3 pts. Construct a 95% Confidence Interval for the proportion of blue M&Ms® candies. 3 pts. Construct a 95% Confidence Interval for the proportion of orange M&Ms® candies. 3 pts. Construct a 95% Confidence Interval for the proportion of green M&Ms® candies. 3 pts. Construct a 95% Confidence Interval for the proportion of yellow M&Ms® candies. 3 pts. Construct a 95% Confidence Interval for the proportion of red M&Ms® candies. 3 pts. Construct a 95% Confidence Interval for the proportion of brown M&Ms® candies. 3 pts. Construct a 95% Confidence Interval for the mean total number of candies (large samples). BONUS: 5 pts. How many candies should be sampled to obtain a 95% CI of the proportion of blue candies with a 4% margin of error if the known proportion of blue candies is 0.24? HELP: Color Proportions You will need the information from the Part 2 Summary. For the colors, the confidence intervals need to be found using the formulas in section 6-3 for proportions. The margin of error formula is is the sample proportion of the color. It will change for each color. is found by 1 - , so it will also change for each color. n is the total number of candies sampled. So let us do an example with “purple”. Let’s say there were 732 purple candies out of 3500 total candies. The sample proportion of purple candies is 732/3500 = 0.209143. This is what you did in part 2. Now to find the confidence interval, we need to calculate E. Let's construct a 95% CI. For that confidence level (95), the z-value is 1.96. We also need : =1- = 1 - 0.209143 = 0.790857. Now let's plug in: The confidence interval is found by - E, +E - E: 0.209143 - 0.013474 = 0.19567 = 19.57% + E: 0.209143 + 0.013474 = 0.22262 = 22.26% So the confidence interval is (0.1957, 0.2226). You will follow this procedure for EACH color. IF you have a TI 83/84, you can do the following: STAT, TESTS, 1-PropZInt, ENTER NOTE: 1-PropZInt: 1 proportion z confidence interval x = total number of that color n = total number of candies Then on the next screen enter 732 next to x, 3500 next to n, 0.95 next to C-Level and then calculate enter. On the next screen the second line is the confidence interval: (0.19567,0.22262) The third line is the value: .2091428571 On the last line is the sample size: 3500 IF you want to use StatCrunch, you will select Stat > Proportions > one sample > with summary. Then it will ask for the number of successes (total number of that color) and number of observations (total number of candies). Click on Next. In the next screen, click on the radio button to the left of “Confidence Interval”, enter the decimal of the confidence level and then click Calculate. The output will have the confidence interval: 95% confidence interval results: p : proportion of successes for population Method: Standard-Wald Proportion Count Total Sample Prop. Std. Err. L. Limit U. Limit P 732 3500 0.20914286 0.006874427 0.19566923 0.2226165 Mean To find the confidence interval for the mean number of candies, you will need (sample mean), s (sample standard deviation) and n. All of these values were summarized on Part 2 Summary. Here n is the number of BAGS sampled. The margin of error formula is IF using the TI 83/84: STAT, TESTS, ZInterval, Enter. Select Inpt: Stats s: enter s value to at least 4 decimal places : enter value to at least 4 decimal places n: enter number of bags sampled C-Level: enter confidence level desired Calculate, ENTER On the next screen the second line is the confidence interval Then and n. IF using StatCrunch, it is best if you copy the num. candies in bag data into StatCrunch, but you can use the summary information. The path is Stat > Z Statistics > one sample > with summary (if using summary information) or with data (if data is entered into the column). If using summary: You will be prompted for the sample mean, sample standard deviation and sample size. Click Next. In the next screen, click the button to the left of Confidence Interval and then enter the confidence level as a decimal and then click Calculate. If using data: You will first select the column with the data, then click next. The next screen is the same as with summary. At the end of this project, you will be writing a report, explaining the method and presenting the results from each part of the project. You might find it useful to write this as you complete the work, so the report will be mostly written by the time it is assigned. MAT 300 M&Ms® Project Part 4 (21 pts) Use the M&Ms® data to complete this assignment. You will be using the methods of 7.4 for the color proportions and 7.2 for the mean number of candies per bag. For the Bonus you will be using the methods of 7.5. You can use StatCrunch to assist with the calculations. A link for StatCrunch can be found under Tools for Success in Course Home. Here is also a link: http://statcrunch.pearsoncmg.com/statcrunch/larson_les4e/dataset/index.html. You can also find additional help on both confidence intervals and StatCrunch in the Online Math Workshop under Tab: “MAT300 Archived Workshops”. Specifically you will be looking for Hypothesis Tests and Using Technology – Hypothesis Testing. Submit your answers in Excel, Word or pdf format. Place the file in the dropbox. Be sure to state clear hypotheses, test statistic values, critical value or p-value, decision (reject/fail to reject), and conclusion in English. When doing calculations for the color proportions, keep at least 4-6 decimal places sample proportions, otherwise you will encounter large rounding errors. Masterfoods USA states that their color blends were selected by conducting consumer preference tests, which indicated the assortment of colors that pleased the greatest number of people and created the most attractive overall effect. On average, they claim the following percentages of colors for M&Ms® milk chocolate candies: 24% blue, 20% orange, 16% green, 14% yellow, 13% red and 13% brown. 3 pts. Test their claim that the true proportion of blue M&Ms® candies is 0.24 at the 0.05 significance level. 3 pts. Test their claim that the true proportion of orange M&Ms® candies is 0.20 at the 0.05 significance level. 3 pts. Test their claim that the true proportion of green M&Ms® candies is 0.16 at the 0.05 significance level. 3 pts. Test their claim that the true proportion of yellow M&Ms® candies is 0.14 at the 0.05 significance level. 3 pts. Test their claim that the true proportion of red M&Ms® candies is 0.13 at the 0.05 significance level. 3 pts. Test their claim that the true proportion of brown M&Ms® candies is 0.13 at the 0.05 significance level. 3 pts. On average, they claim that a 1.69 oz bag will contain more than 54 candies. Test this claim (µ > 54) at the 0.01 significance (σ unknown). BONUS: 5 pts. It is important that the total number of candies per bag does not vary very much. As a result of this quality control, the desired standard deviation is 1.5. Test the claim (α = 0.05) that the true standard deviation for number of candies per 1.69 oz bag is no more than 1.5 (σ < 1.5). HELP: Color proportions Revisiting the purple example from before: we had 732 purple candies out of 3500 total candies. The sample proportion of purple candies is 732/3500 = 0.2091428571. Now let's say you want to test that the true proportion of purple candies is 21% (0.21). First define your hypotheses. Claim: p = 0.21 H0: p = 0.21 (null) H1: p ≠ 0.21 (alternative) Next we need to calculate the test statistic. For this type of test, it is a z and a two tailed test. You have been asked to test at alpha = 0.05, so we will reject the null if the test statistic, z, is positive and greater than 1.96 OR if the test statistic, z, is negative and smaller than -1.96. (NOTE: This is the same as if the absolute value of the test statistic is greater than 1.96.) Review: → sample proportion (0.209143) p → assumed value in null (0.21) q → 1 - p (0.79) n → total number of candies (3500) Test statistic: Because the test statistic is between -1.96 and 1.96, we FAIL TO REJECT. We have insufficient evidence to suggest the true proportion is not 0.21. You will follow this procedure for EACH color. IF using the TI 83/84: STAT, TESTS, 1-PropZTest Po: assumed proportion (0.21) x: number of successes (732) n: total number of candies (3500) In the next line, select the correct alternative hypothesis/test, then Calculate, Enter. On the next screen, the second line shows the test. The next line has the test statistic. The next line has the p-value of the test (if less than significance level, reject null) The next two lines have and n. IF using StatCrunch, you will want Stat > Proportions > One Sample > with summary. In the first window, you will enter the same information as for part 3: number of the color (number of successes) and total number of candies (number of observations). Then click Next, and in the following window, enter the claimed proportion as a decimal in the box next to “null”, select the inequality that matches the alternative hypothesis and then click Calculate. The output will include the test statistic (Z-Stat) and the p-value. Hypothesis test results: p : proportion of successes for population H0 : p = 0.21 HA : p ≠ 0.21 Proportion Count Total Sample Prop. Std. Err. Z-Stat P-value p 732 3500 0.20914286 0.006884766 -0.12449848 0.9009 Mean When you test for the mean number of candies per bag, you will need (sample mean), s (sample standard deviation) and n (total number of bags) as before. The test statistic is a z, because we have a large sample. Test statistic: IF using the TI 83/84: STAT, TESTS, Z-Test Input: Stats 0: assumed mean value : sample or known standard deviation : sample mean N: sample size Then select the correct alternative hypothesis/test, then Calculate, Enter. On the next screen, the second line shows the test. The next line has the test statistic. The next line has the p-value of the test (if less than significance level, reject null) The next two lines have and n. IF using StatCrunch, you will use Stat > Z Statistics > one sample as with part 3. BONUS This is a test about a standard deviation. You can use StatCrunch, however, StatCrunch deals with variances, so you would enter 1.5² = 2.25 as the null value. You would use Stat > Variance > One Sample. Again, it would be best to use the actual data entered into a column, but you can also use summary values, as long as you carry at least 4 decimal places. At the end of this project, you will be writing a report, explaining the method and presenting the results from each part of the project. You might find it useful to write this as you complete the work, so the report will be mostly written by the time it is assigned. M&Ms® Project Part 5 (3 pts) Using the methods in Section 8.4, test the hypothesis (α = 0.05) that the population proportions of red and brown are equal (pred = pbrown). You are testing if their proportions are equal to one another, NOT if they are equal to one another AND equal to 13%. NOTE: These are NOT independent samples, but we will use this approach anyway to practice the method. This also means that n1 and n2 will both be the total number of candies in all the bags. The “x” values for red and brown are the counts of each we found on the Data page. You will need to calculate the weighted p: Be sure to state clear hypotheses, test statistic, critical value or p-value, decision (reject/fail to reject), and conclusion in English. Submit your answer as a Word, Excel, .rtf or .pdf format and place in the dropbox. HELP You can use StatCrunch or the TI to help with this test. Needed information for both tools include: x1 = number of red n1 = total number of candies x2 = number of brown n2 = total number of candies For the TI, you will want 2-PropZTest. Then select the appropriate alternative (not equal), and Calculate then enter. The output will have the test statistic (z), p-value (p), sample p values, weighted p ( ), then repeat of sample sizes. For StatCrunch, you will select Stat > Proportions > Two Sample > with summary. The output will contain the test statistic (Z-Stat) and p-value. Additional help is available in the Online Math Workshop under MAT300 Archived Workshop. Specifically Two Sample Inferences and Using Technology – Two Sample. At the end of this project, you will be writing a report, explaining the method and presenting the results from each part of the project. You might find it useful to write this as you complete the work, so the report will be mostly written by the time it is assigned. M&Ms® Project Report (15 pts) A template report file can be found in the course shell: mnmprojectreport.doc. Before your write your report, watch the video titled “mnmunwrapped.wmv” located in the course shell. It is a 3:30-minute video segment from the TV show “Unwrapped,” showing many parts of the production process, which might give you some ideas. Ignore the color percentages quoted in the segment. Imagine you are a quality control manager at the Masterfoods plant. Write a two to three (2–3) page report on all the parts of the project. Structure your paper using the following headers: o Introduction: Purpose of Report o Project Part 1: Sampling Method o Project Part 2: Method, Analysis, Results o Project Part 3: Method, Analysis, Results o Project Part 4: Method, Analysis, Results o Project Part 5: Method, Analysis, Results o Quality Control: Assume that at least one of the tests from Part 4 was rejected (proportion not equal to targeted amount set by Masterfoods). Discuss how you would investigate the operations of the plant to determine why the proportions were off the targeted values. Speculate on three or more possible conditions in plant and bagging process that could have caused the observed results. o Conclusion You should explain what was done as well as the results. Tables can be used to present results and information. Your audience is a supervisor or manager who is unfamiliar with this project and may or may not be familiar with statistical terms. As a result, you will either need to explain/define statistical terms or write them in a way that a layman can understand. You will be graded on the following criteria: 1. Present the methods, analysis, and results for the five parts of the project. See above Project Parts 1 through 5. 2. Explain how to investigate unexpected results (failed test(s) in Part 4) and speculate on at least three plausible causes for the observed results. 3. Clarity in explaining all statistical terminology in every-day language. 4. Writing, grammar, sentence structure, APA format. The format of the report is to be as follows: o Typed, double-spaced, Times New Roman font (size 12), one-inch margins on all sides, APA format. o Type the question followed by your answer to the question. o In addition to the two to three (2–3) pages required, a title page is to be included. The title page is to contain the title of the assignment, your name, the instructor’s name, the course title, and the date. NOTE: You will be graded on the presentation of information, the accuracy and completeness of your answers, the logic/organization of the report, the clarity of your explanations, and your writing skills (grammar, style, spelling, etc.) The assignment will be graded using the following rubric and is worth 6% of course grade: Discuss application of course content in the context of a professional setting. Outcomes Assessed Use technology and information resources to research issues in statistics. Grading Rubric for M&M® Project Report 0 10 20 30 Criteria Unacceptable Developing Competent Exemplary 1. Present the Did not submit or Partially presented Sufficiently Fully presented the methods, analysis, did not present the the methods, presented the methods, analysis, and results for the methods, analysis, analysis, and results methods, analysis, and results for the five parts of the and results for the for the five parts of and results for the five parts of the project. five parts of the the project; five parts of the project; completed project; or omitted completed project; completed with 90-100% key information with 60-79% with 80-89% accuracy and and/or included accuracy and accuracy and thoroughness. irrelevant thoroughness. thoroughness. information. Completed with less than 60% accuracy, thoroughness, and logic. 2. Explain how to Did not complete Partially explained Sufficiently Fully explained how investigate the assignment or how to investigate explained how to to investigate unexpected results failed to explain unexpected results investigate results unexpected results (failed test(s) in how to investigate and speculated on at and speculated on at and speculated on at Part 4) and unexpected results least one plausible least two plausible least two plausible speculate on at or to speculate on cause; completed causes; completed causes; completed least three plausible causes; or with 60-79% with 80-89% with 90-100% plausible causes omitted key accuracy and accuracy and accuracy and for the observed information and/or thoroughness. thoroughness. thoroughness. results. included irrelevant information. Completed with less than 60% accuracy, thoroughness, and logic. 3. Clarity: Explain Did not complete Explained partially Explained Explained fully all all statistical the assignment or all statistical sufficiently all statistical terminology in did not explain all terminology in statistical terminology in every-day statistical every-day language terminology in every-day language; language. terminology in or explained every-day language; completed with 90- every-day language. sufficiently some of completed with 80- 100% accuracy and ; or omitted key the statistical 89% accuracy and thoroughness. information and/or terminology in thoroughness. included irrelevant every-day language; information. completed with 60- Completed with less 79% accuracy and than 60% accuracy, thoroughness. thoroughness, and logic. 4. Writing – Did not complete Had 6 - 7 different Had 4 - 5 different Had 0 - 3 different Grammar, the assignment or errors in grammar, errors in grammar, errors in grammar, sentence structure, had 8 or more sentence structure, sentence structure, sentence structure, paragraph different errors in paragraph structure, paragraph structure, paragraph structure, structure, spelling, grammar, sentence spelling, spelling, spelling, 0 10 20 30 Criteria Unacceptable Developing Competent Exemplary punctuation, APA structure, paragraph punctuation, or punctuation, or punctuation, or usage. structure, spelling, APA usage. (Many APA usage. (Minor APA usage. punctuation, or issues) issues) APA usage. (Major issues)