Presentation on theme: "Enhancing Your Students’ Conceptual Understanding of Statistics"— Presentation transcript:
1Enhancing Your Students’ Conceptual Understanding of Statistics Michael SullivanJoliet Junior College
2GAISE (Guidelines for Assessment and Instruction in Statistics Education)Six RecommendationsEmphasize statistical literacyI am going to expand this to statistical literacy, statistical reasoning, and statistical thinkingUse real dataStress conceptual understanding rather than knowledge of proceduresFoster active learningUse technology for developing conceptual understanding and analyzing dataUse assessments to improve and evaluate student learning
3A Recommendation on the First Day of Class You are not in a math class!!!!!!
4What is Conceptual Understanding? The ability to interpret and explain resultsThe ability to determine which techniques are appropriateDe-emphasis of procedural methodsTeach fewer concepts, and dig deeperWe are trying to teach too much material in our statistics courses.
9May want to talk about how increasing sample size affects the precision of results as a prelude to the Law of Large Numbers. Also, compare sampling with nonsampling error.
10The Golden RatioMeasure the height of your partner in centimeters. Call this y.Measure the height to your partners naval. Call this x. (We could also measure arm span)Draw a scatter diagram of the data treating height to naval (arm span) as the explanatory variable.Find the least-squares regression line treating height to naval as the explanatory variable.What is the slope? Interpret the slope.Does it make sense to interpret the intercept? Why?
11Emphasize Statistical Literacy Statistical literacy involves understanding and using the basic language and tools of statistics: knowing what statistical terms mean, understanding the use of statistical symbols, and recognizing and being able to interpret representations of data.Source: ARTIST website
12Examples of Problems/Questions that Demonstrate Statistical Literacy Suppose you have just constructed a 95% confidence interval. Name two options for increasing the precision of the interval.Draw a scatter diagram for which r = 1.According to popcorn.org, the mean consumption of popcorn annually by Americans is 54 quarts. The marketing division of popcorn.org unleashes an aggressive campaign designed to get Americans to consume even more popcorn. After two months, it was concluded that the marketing campaign was effective. Suppose, in fact, that the actual mean consumption of popcorn after the marketing campaign is 53.4 quarts. What type of error was committed? Why?What is an observational study? What is a designed experiment? Which allows the researcher to claim causation between an explanatory variable and a response variable?Explain what is meant by confounding. What is a lurking variable?What is resistance? Is the mean resistant? The median? Is the standard deviation resistant?
13Emphasize Statistical Reasoning Statistical reasoning is the way people reason with statistical ideas and make sense of statistical information. Statistical reasoning may involve connecting one concept to another (e.g., center and spread) or may combine ideas about data and chance. Reasoning means understanding and being able to explain statistical processes, and being able to fully interpret statistical results.Source: ARTIST website
14Examples of Problems/Questions that Demonstrate Statistical Reasoning In clinical trials of Nasonex, 3774 adult and adolescent allergy patients (patients 12 years old and older) were randomly divided into two groups. The patients in group 1 (experimental group) received 200 µg of Nasonex, while the patients in group 2 (control group) received a placebo. Of the 2103 patients in the experimental group, 547 reported headaches as a side effect. Of the 1671 patients in the control group, 368 reported headaches as a side effect. Is there significant evidence to conclude that the proportion of Nasonex users that experience headaches as a side effect is greater than the proportion in the control group? Are the results practically significant?The Food and Drug Administration sets Food Defect Action Levels (FDALs) for some of the various foreign substances that inevitably end up in the food we eat and liquids we drink. For example, the FDAL for insect filth in peanut butter is 3 insect fragments (larvae, eggs, body parts) per 10 grams. A random sample of 50 ten-gram portions of peanut butter is obtained and results in a sample mean of 3.6 insect fragments per ten-gram portion. Describe the sampling distribution of the sample mean.
15Examples of Problems/Questions that Demonstrate Statistical Reasoning Stocks may be categorized by industry. The following data represent the 5-year rates of return (in percent) for a sample of financial stocks and energy stocks ending December 3, Which sector is riskier? Does the sector with the higher risk, reward its investors? Why?
16Examples of Problems/Questions that Demonstrate Statistical Reasoning The following data represent the weights of plain M&Ms candies. Describe the distribution of weights. Which measure of central tendency is most appropriate to report? Which measure of dispersion is most appropriate to report? Justify your recommendations.
17Examples of Problems/Questions that Demonstrate Statistical Reasoning Suppose 100 different researchers wish to estimate the mean amount of time (in hours) 18 – 24 year old males spend watching television each week. Each researcher surveys a random sample of forty 18 – 24 year old males and constructs a 95% confidence interval for the mean time (in hours) 18 – 24 year old males watch television each week. How many of these intervals do we expect to capture the population mean?
18Emphasize Statistical Thinking Statistical thinking involves an understanding of why and how statistical investigations are conducted. This includes recognizing and understanding the entire investigative process (from question posing to data collection to choosing analyses to testing assumptions, etc.), understanding how models are used to simulate random phenomena, understanding how data are produced to estimate probabilities, recognizing how, when, and why existing inferential tools can be used, and being able to understand and utilize the context of a problem to plan and evaluate investigations and to draw conclusions.Source: ARTIST website
19Examples of Problems/Questions that Demonstrate Statistical Thinking What makes this a designed experiment? What type of experimental design is this?What is the response variable? Is it qualitative or quantitative?What factors are controlled in the experiment?In many experiments, the researcher will recruit volunteers and randomly assign the individuals to a treatment group. In what regard was this done for this experiment?Did the students perform better on the final exam in the fall semester?Can you think of any factors that may confound the results?Shows many facets of the statistical process
20Examples of Problems/Questions that Demonstrate Statistical Thinking Requires students to report the statistical process and contrast the study to what would occur in a designed experiment.
21These are thinking problems because we don’t tell the student what type of test to use. The student must identify the correct procedure, verify the requirements of the procedure, do the test, and report the results.
22What does GAISE say about being statistical literate? See the GAISE report pages 5 – 7Consider their carpentry analogy:In week 1 of the carpentry (statistics) course we learned to use various kinds of planes (summary statistics). In week 2 we learned to use different kinds of saws (graphs). Then we learned about using hammers (confidence intervals). Later we learned about the characteristics of different types of wood (tests). By the end of the course we had covered many aspects of carpentry (statistics). But I wanted to learn how to build a table (collect and analyze data to answer a question) and I never learned how to do that.Most of us probably use projects with the goal that students synthesize the material in the course and learn the statistical process. Personally, I have been disappointed in the students’ ability to create a project that demonstrates their understanding of the statistical process and their ability to recognize when certain procedures (conf int or hypothesis test) are desired, or applicable. Our students need more practice during the semester deciding what methods to use, or seeing how the various techniques are related to each other.“Many introductory courses contain too much material and students end up with a collection of ideas that are understood only at a surface level, are not well integrated and are quickly forgotten.”- Page 10, the GAISE report
23Using Technology to Enhance Students’ Conceptual Understanding - Applets Correlation by eye appletDraw a scatter diagram where the correlation of the data is about 0.8.Draw two scatter diagrams where the correlation of the data is close to 0.Draw a scatter diagram with about 6 points where the correlation is about Now add another point and move it around the Cartesian plane. How does this single point impact the value of the correlation coefficient?Regression by eye appletDraw a scatter diagram where the explanatory and response variable are negatively associated. Compare SSE for the regression line to an “eye-balled” line.Draw a scatter diagram where the explanatory and response variable are positively associated. Add another point that may be influential. How does this point impact the slope and/or intercept?Confidence interval appletUsing either the proportion or mean confidence interval applet, illustrate the meaning of “level of confidence”Using either the proportion or mean confidence interval applet, illustrate the impact of not meeting the model requirements on the proportion of intervals that capture the parameter.
24Using Technology to Enhance Students’ Conceptual Understanding - Simulations Illustrate the sampling distribution of the sample mean using MINITAB.
25Advantages of Personal Response Systems Increased attentionIncreased attendanceIncreased retentionDraper and BrownStudents are twice as likely to attempt to construct an answer to a question using a PRS compared to a question that required them to raise their hand.
27Types of Questions Multiple Choice True/False Numeric Series Short AnswerSurveyBe sure to show the audience how each question is constructed using the PRS PowerPoint plug-in.
28Multiple ChoiceFrom what kinds of variables would side-by-side boxplots be generated?Qualitative onlyQuantitative onlyOne qualitative and one quantitativeTwo quantitativeNot sure
29Free ResponseThe reading speed of sixth-grade students is approximately normal, with a mean speed of 125 words per minute and a standard deviation of 24 words per minute. What is the probability that a randomly selected sixth-grade student reads less than 100 words per minute?
30SeriesThe following represent the steps in the statistical process. Put them in the correct order.Draw conclusions from the informationIdentify the research objectiveOrganize and summarize the informationCollect the information needed to answer the research questions
31Camtasia VideosAsk students to watch the lecture at home…then class can be dedicated to developing the students conceptual understanding
32Sources ARTIST website (https://app.gen.umn.edu/artist/index.html) Chance, Beth L. (2002) Components of Statistical Thinking and Implications for Instruction and Assessment. Journal of Statistics Education 10, No. 3delMas, Robert C. (2002) Statistical Literacy, Reasoning, and Learning: A Commentary. Journal of Statistics Education 10, No. 3Draper, S. and Brown, M. (2004) Increasing interactivity in lectures using an electronic voting system. Journal of Computer Assisted Learning 20, 81 – 84Draper, S. , Cargil, J. and Cutts, Q. (2002) Electronically enhanced classroom interaction. Australian Journal of Educational Technology 18, 13 – 23Ebert-May, D., Brewer, C. and Allred, S. (1997) Innovation in large lectures—teaching for active learning BioscienceGAISE College Report (www.amstat.org/education/gaise/)Garfield, Joan (2002) The Challenge of Developing Statistical Reasoning. Journal of Statistics Education 10, No. 3Hake, R. (1997) Interactive-engagement vs traditional methods: A six-thousand student survey of mechanics test data for introductory physics courses. American Journal of PhysicsKennedy, G.E. and Cutts, Q.I. (2005) The association between students’ use of an electronic voting system and their learning outcomes. Journal of Computer Assisted Learning – 268Rumsey, Deborah (2002) Statistical Literacy as a Goal for Introductory Statistics Courses. Journal of Statistics Education 10, No. 3West, J. (Dec. 9, 2005) Learning outcomes related to the use of personal response systems in large science courses. Academic Commons.Wit, E. (2003) Who wants to be… The use of a personal response system in statistics teaching. MSOR Connections