Students practice using pedometers. Students will walk 264 feet, one-twentieth of a mile, while wearing a pedometer. They will
investigate if there is a significant difference between the number of steps recorded by a Dollar Store pedometer and a pedometer App.

Students will explore real data collected on the completion of a maze. Through the two-sample independent -test, students will test to see if the mean time to complete the maze is significantly different for males compared to females.

This lesson introduces students to bootstrapping methods for making inferences about a population parameter using a randomly selected sample from the population. Students use random samples of salaries for petroleum engineering graduates - —graduates employed in the profession earning the highest mean starting salary in 2014 - —and technology tools to calculate and interpret interval estimates for the mean population starting salary. They also explore the effects of sample size and confidence level on margin of error. Students draw conclusions using both the context of the activity and bootstrapping distributions generated from simulations. Students’ explorations conclude with drawing inferences about a population proportion.

In this activity, students conduct an investigation to determine which of four chocolate candies is preferred. Each student will taste one each of four candies and will rate them from most to least favorite. Students will then construct a picture graph and a bar graph to determine which types of chocolate were selected as the most and least favorite. Students will also generate a method to decide which candy was the overall class favorite. Conclusions are drawn based on the analysis in the context of the question(s) asked.

Students have the opportunity to collect and explore real data using a box of animal crackers.

In this lesson, students will analyze and explore the data collected in the cell phone experiment. Graphs such as boxplots and comparative boxplots are drawn to illustrate the data. Measures of center (median, mean) and spread (range, Interquartile Range (IQR)) are computed. Outlier checks are performed. The distinction between independent samples and paired (matched) samples is discussed. Conclusions are drawn based upon the data analysis in the context of question(s) asked. An extension to a randomization test (permutation test) is discussed.

Students will analyze an advertisement and survey of a new product. Looking at the survey, graphs, and claims the company made, students will determine if they are biased or fair and determine if the information was misrepresented or not.

Students will learn the concepts of a two-sample randomization test, conduct tactile and computer simulations, and interpret this probability in the context of the problem.

Students collect data from an experiment designed to investigate whether or not the ability to name the color of printed ink is challenged when the word written with the ink is the name of a color.

Students will determine if drinking cola increases heart rate. The primary purpose of the lesson is to look for extraneous variables and try to control them through focusing on experimental design.

Students will use statistics to determine whether there is evidence that Double Stuf Oreos have double the filling as Regular Oreos.

Random sampling is used to estimate the proportion of the Earth's surface that is covered with water.

Students will have the opportunity to collect and explore data. Students will perform an experiment in order to test The Psychic Staring Effect. The Psychic Staring Effect is the idea that people can sense that they are being stared at.

In this activity students will have the opportunity to collect and explore data. Students will perform an experiment in order to test The Psychic Staring Effect. The Psychic Staring Effect is the idea that people can sense that they are being stared at. The activity can be used to illustrate large-sample confidence intervals and hypothesis tests on proportions; two-way table analysis and the chi-square test; the binomial distribution and the binomial test.

Data collected by students is used to estimate the area of an irregularly shaped threedimensional object using sampling, sampling variability of the sample mean, and confidence interval estimation.

This lesson plan includes an interactive activity to illustrate various sampling methods. Using the periodic table of elements, students will collect real data implementing simple random and systematic sampling. With both samples collected, students will calculate appropriate descriptive statistics and use the sampling distributions to compare the performance of the methods.

Using the periodic table of elements, students will collect real data implementing simple random and systematic sampling. With both samples collected, students will calculate appropriate descriptive statistics and use the sampling distributions to compare the performance of the methods.

This lesson introduces students to randomization tests for making inferences about a population parameter using a randomly selected sample from the population. Students use random samples of salaries for petroleum engineering graduates and technology tools to conduct a significance test to determine whether petroleum engineering graduates after 2014 suffered lower starting salaries in alignment with falling crude oil prices than the 2014 population mean starting salary of petroleum engineering graduates. They also explore connections between significance tests and confidence intervals. Students draw conclusions using both the context of the activities and one- sided and two-sided randomization tests using simulations.

In this lesson, students will collect their own data and visualize the distribution of the data by creating dotplots and generating comparative boxplots from the dotplot visualizations. They will also have an opportunity on comparing and contrasting visualizations to learn advantages and disadvantages of these two visualizations.

This activity allows students to set up a statistical question to explore a population parameter of interest and, more specifically, perform a hands-on investigation to investigate a claim about a population proportion.