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** Sampling from a Real Estate Database

This material is a detailed exercise for students in introductory statistics. Students are asked to collect a random sample of data from a real estate website; conduct descriptive statistics (including confidence intervals); and write a report summarizing their dataset. The primary learning goals are to teach students 1) how to obtain a random sample; 2) how to interpret confidence intervals; 3) how to simulate and interpret a sampling distribution; and 4) how to communicate descriptive statistics.
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Date Of Record Creation 2005-03-21 16:19:00
Date Last Modified 2013-01-21 16:16:00
Date Of Record Release 2005-03-21 16:19:00
Email Address woodard@stat.ncsu.edu
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Author Name Roger Woodard
Author Organization Department of Statistics, North Carolina State University
Comments If I were teaching a course in introductory statistics next semester, I would absolutely use this exercise. My only comment is that I would probably change the dataset in the exercise to match my student population. While my evening MBA students might find the real estate dataset interesting, my undergraduates might prefer to visit a website on sports, crime, education, etc.
Content Quality (Concerns) This material asks students to make use of the one-sample z methods based on the assumption that the sample standard deviation equals the population standard deviation. Instructors who prefer to use methods based on the t-distribution may wish to rewrite the material accordingly. Instructors should also be cautioned that the assumptions for using the normal appoximation to the binomial will not be satisfied for some of the categorical variables.
Content Quality (Strengths) A major strength is the use of real data to assist in motivating students and providing a real-world application of statistics. The integrated nature of the assignment from data collection through report writing is a strength. The focus on correct interpretation of confidence intervals is an important topic for the target audience. The assignment is well integrated with the web source for the data including an illustration of one data record. This exercise is clear, well-written and well-structured. Students should find it easy to follow. In addition, the screen shots of Minitab make the computer instructions clear. Finally, the inclusion of a scoring rubric make this a complete exercise.
Ease of Use (Concerns) This material is written for a specific software (Minitab) and instructors who do not have access to this software will need to do a substantial rewrite of the material, as will those who have a different version of the software.
Ease of Use (Strengths) Students and faculty should find the materials easy to us because the assignment is well integrated with screen shots of the data source and Minitab. Examples of input are provided as well as hints and tips, a grading rubric and instructor notes, and discussion points. The combination of the clarity of the exercise and scoring rubric should make this statisitcs mini-project easy to use by both students and faculty.
Potential Effectiveness (Concerns) The data entry portion of the assignment may become burdensome if all the variables identified are required. Also, it is possible some students may have inconsistencies in data entry within their dataset causing confusion. Instructors may wish to have students verify their data prior to completing the final report. Instructors may also want to make expectations more clear by making the grading rubric available to them.
Potential Effectiveness (Strengths) This could be a very effective tool for demonstrating the correct interpretation of confidence intervals using real data. Students should also learn the importance of careful data entry, data quality control, and statistical software. The combination of the concepts of random sampling, confidence intervals and sampling distributions make it powerful as a teaching tool.
Content Quality (Rating) 4
Ease of Use (Rating) 4
Potential Effectiveness (Rating) 5
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Statistical Topic
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