Introduction to Statistics Project Description The Project is divided into three parts, with separate due dates. If any part of the Project is turned in late, a point will be taken off the Project grade each day. If any errors are found on any of the parts of the Project, they may be corrected and turned in again with the next part, up until the final deadline. Projects may be completed by hand or typed. They may be turned in as a hard copy in class, slipped under my office door, or sent electronically, by 5pm the day they are due. See the Grading Rubric at the end of this document for how points will be awarded. Up to 5 points in extra credit may be awarded for work that is especially well done, attractive, or innovative. You can get an extra credit point for using the Dropbox for all submissions. You can get another extra credit point for having everything – graphs, Greek letters, everything – in electronic form (not hand written). The last day to turn in any part of the Project is December 1st. Part 1 Due: September 3 • Write two numerical questions that have something to do with each other. • Ask 15 men and 15 women both questions. o Create a table of your data. • Write a paragraph about forms of bias that might be found in your data, using the vocabulary we learned in class. • Create histograms (one for each question, using all 30 data points, men and women together). o Label axes or state your window. • Create boxplots (one for each question, using all 30 data points, men and women together). o Label axes or state your window. • Compute o the mean for each question o the standard deviation for each question o the five-number summary for each question. • Write a sentence for each question, describing the shape of the distribution, and giving the value of any outliers (or stating that there are no outliers). • Write a sentence for each question describing the central tendency of your data, using the appropriate numerical summary and units (years, dollars, etc., don’t just give numbers). Statistics Project Description Part 2 Due: October 27 Include Part 1 with your submission, if you made corrections. • For each of your questions, find a 90% confidence T-interval for the mean of all 30 values (men and women together). Use PAIME. • For each of your questions, devise an appropriate T-test to compare the mean of all 30 values (men and women together) against a number you choose. Use PHANTASM. • For each of your questions, compare women to men by finding a 90% confidence 2-Sample T-Interval. Use PAIME. • For each of your questions, compare women to men using a 2-Sample T-Test. Use PHANTASM. • Compare your two questions by performing linear regression. o State which question is the explanatory variable and which is the response variable. o Give the linear regression equation. o Show a graph of the data points with the linear regression line. o Write a sentence explaining what the slope of the linear regression line means in terms of your two questions, with numbers and units. o Write a sentence explaining what the y-intercept of the linear regression line means in terms of your two questions, with numbers and units. o Write a sentence explaining what r means, including if the relationship between your questions is positive or negative, and how strong the relationship is. o Write a sentence explaining what r2 means in terms of your two questions, with units. Statistics Project Description Part 3 Due: November 17 Include any previous parts, whether or not you have made changes to them. • Write an “executive summary” about your project. This is a paragraph or two that sums up everything you found. This can be partly the sentences you’ve written for other parts, but also needs to bring it all together and talk about if the results were surprising, or exactly what you expected. Think about what you would like to know about your topics, why you chose those questions in the first place. For example, if you asked people their age and their height, your executive summary might include the average age and height of men, women, and both together; whether or not there is a significant difference between the age or height of men and women; and what sort of relationship the linear regression showed there is between age and height.

Subject | Mathematics |

Due By (Pacific Time) | 09/02/2015 12:00 am |

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