Taming the AP Statistics Investigative Task Daren Starnes The Lawrenceville School CMC South Oct 2015

AP Statistics Teachers Meeting In this room at 12:30. Grab a bite to eat and come join us for a panel discussion and some fabulous give- aways from the publishers.

Who are we? Please raise your hand if you… –Are an AP Statistics teacher –Are a high school, non-AP statistics teacher –Are a college intro stats instructor –Have taught statistics for 0-1 years –Have taught statistics for 2-4 years –Have taught statistics for 5-9 years –Have taught statistics for 10 or more years –Have graded AP Statistics exams –Want to get this workshop started!

The Investigative Task “In the free-response section of the AP Statistics Exam, students are asked to answer five questions and complete an investigative task. Each question is designed to be answered in approximately 12 minutes. The longer investigative task is designed to be answered in approximately 30 minutes. The purpose of the investigative task is not only to evaluate the student’s understanding in several content areas but also to assess his or her ability to integrate statistical ideas and apply them in a new context or in a nonroutine way.” AP Statistics Course Description

Why are we here? The Investigative Task counts for 25% of a student’s Free Response section score. How can we prepare our students to successfully do the kind of outside-the-box thinking that is required on the investigative task?

2011 Exam (Form B) Question 6 6. Grass buffer strips are grassy areas that are planted between bodies of water and agricultural fields. These strips are designed to filter out sediment, organic material, nutrients, and chemicals carried in runoff water. The figure below shows a cross-sectional view of a grass buffer strip that has been planted along the side of a stream.

2011 Exam (Form B) Question 6

Part (a)

Part (b) (b) Would you be willing to use this model to predict the amount of nitrogen removed for grass buffer strips with widths between 0 feet and 30 feet? Explain why or why not. No. This is extrapolation beyond the range of data from the experiment. Buffer strips narrower than 5 feet or wider than 15 feet were not investigated.

Now things get interesting…

The Big Idea behind parts (c) and (d)

Part (c)

Part (d) (d) Using your result from part (c), show how to construct an interval that has probability 0.95 of containing the sample mean of the observations from four buffer strips with widths of 6 feet. The distribution of the sample mean is normal, so the interval that has probability 0.95 of containing the mean nitrogen content removed from four buffer strips of width 6 feet extends from × 2.5 = 50.5 parts per hundred to × 2.5 = 60.3 parts per hundred.

And for the next twist… For the study plan being implemented by the scientist in California, the graph on the left below displays intervals that each have probability 0.95 of containing the sample mean of the four observations for buffer strips of width 6 feet and for buffer strips of width 13 feet. A second possible study plan would use buffer strips of width 8 feet at four of the eight locations and buffer strips of width 10 feet at the other four locations. Intervals that each have probability 0.95 of containing the mean of the four observations for buffer strips of width 8 feet and for buffer strips of width 10 feet, respectively, are shown in the graph on the right below.

If data are collected for the first study plan, a sample mean will be computed for the four observations from buffer strips of width 6 feet and a second sample mean will be computed for the four observations from buffer strips of width 13 feet. The estimated regression line for those eight observations will pass through the two sample means. If data are collected for the second study plan, a similar method will be used.

Part (e) (e) Use the plots above to determine which study plan, the first or the second, would provide a better estimator of the slope of the regression line. Explain your reasoning.

Part (e) Solution

Part (f) (f) The previous parts of this question used the assumption of a straight-line relationship between the width of the buffer strip and the amount of nitrogen that is removed, in parts per hundred. Although this assumption was motivated by prior experience, it may not be correct. Describe another way of choosing the widths of the buffer strips at eight locations that would enable the researchers to check the assumption of a straight-line relationship.

Part (f) Solution To assess the linear relationship between width of the buffer strip and the amount of nitrogen removed from runoff water, more widths should be used. To detect a nonlinear relationship, it would be best to use buffer widths that were spaced out over the entire range of interest. For example, if the range of interest is 6 to 13 feet, eight buffers with widths 6, 7, 8, 9, 10, 11, 12 and 13 feet could be used.

Intermission?! What are some strategies we can use to help our students develop competence and confidence with investigative tasks like this one?

2009 Exam Question 6 A consumer organization was concerned that an automobile manufacturer was misleading customers by overstating the average fuel efficiency (measured in miles per gallon, or mpg) of a particular car model. The model was advertised to get 27 mpg. To investigate, researchers selected a random sample of 10 cars of that model. Each car was then randomly assigned a different driver. Each car was driven for 5,000 miles, and the total fuel consumption was used to compute mpg for that car.

Part (a) (a)Define the parameter of interest and state the null and alternative hypotheses the consumer organization is interested in testing. The parameter of interest is µ = population mean miles per gallon (mpg) of a particular car model. The null and alternative hypotheses are as follows:

One condition for conducting a one-sample t-test in this situation is that the mpg measurements for the population of cars of this model should be normally distributed. However, the boxplot and histogram shown below indicate that the distribution of the 10 sample values is skewed to the right.

Part (b)

Part (c) Even though the mpg values in the sample were skewed to the right, it is still possible that the population distribution of mpg values is normally distributed and that the skewness was due to sampling variability. To investigate, 100 samples, each of size 10, were taken from a normal distribution with the same mean and standard deviation as the original sample.

Part (c)

Based on the value of 1.03 and the dotplot above, is it plausible that the original sample of 10 cars came from a normal population, or do the simulated results suggest the original population is really skewed to the right? Explain.

Part (c) Solution Because we are testing for right-skewness, the estimated p-value will be the proportion of the simulated statistics that are greater than or equal to the observed value of The dotplot shows that 14 of the 100 values are more than Because this simulated p-value (0.14) is larger than any reasonable significance level, we do not have convincing evidence that the original population is skewed to the right and conclude that it is plausible that the original sample came from a normal population.

Part (d) The table below shows summary statistics for mpg measurements for the original sample of 10 cars. Choosing only from the summary statistics in the table, define a formula for a different statistic that measures skewness. What values of that statistic might indicate that the distribution is skewed to the right? Explain.

Part (d) Solution

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