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.
The Advanced Data Grapher can be used to analyze data with box plots, bubble graphs, scatterplots, histograms, and stem-and-leaf plots. You can enter multiple rows and columns of data, select which set(s) to display in a graph, and choose the type of representation.
This task was developed by high school and postsecondary mathematics and health sciences educators, and validated by content experts in the Common Core State Standards in mathematics and the National Career Clusters Knowledge & Skills Statements. It was developed with the purpose of demonstrating how the Common Core and CTE Knowledge & Skills Statements can be integrated into classroom learning - and to provide classroom teachers with a truly authentic task for either mathematics or CTE courses.
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 calculate various measures of central tendency using data on the number of people who bike to work in select states. Students will then create a box plot to represent the data set and answer conceptual questions about the impact of the data set's outlier.
In this Khan Academy activity, students will represent data with plots, interpret differences in shape, center, and spread in the context of the data sets, and examine the effects of extreme data points (outliers) on shape, center, and/or spread.
Students compare two or more distributions in terms of center, variability, and shape; Students interpret a measure of center as a typical value; Students interpret the IQR as a description of the variability of the data; Students answer questions that address differences and similarities for two or more distributions.
Students construct a dot plot from a data set; Students calculate the mean of a data set and the median of a data set; Students observe and describe that measures of center (mean and median) are nearly the same for distributions that are nearly symmetrical; Students observe and explain why the mean and median are different for distributions that are skewed; Students select the mean as an appropriate description of center for a symmetrical distribution and the median as a better description of center for a distribution that is skewed.
Students will develop a set of tools for understanding and interpreting variability in data, and begin to make more informed decisions from data. They work with data distributions of various shapes, centers, and spreads. Students build on their experience with bivariate quantitative data from Grade 8. This module sets the stage for more extensive work with sampling and inference in later grades.
Students collect sample data from their class to estimate the
median foot size of the population of students in the class. Each student obtains a point
estimate and constructs an interval estimate for the median foot size in the entire class by using a
simple random sample of 10 students in the class. Numeric summaries (mean and five-number
summary) and box plots are used to obtain point and interval estimates, respectively, for the
median foot size of the entire class. The teacher records the foot size of all students in class in
order to obtain the population median foot size of the entire class. The confidence level, or
reliability, for the interval estimates computed by the students is estimated by obtaining the
proportion of students' sample interval estimates that trap the population median foot size of the
entire class. In the second part of this activity, students use online statistical software to explore
relationships between both different sample sizes and different shapes of a population
distribution, and the variability in bounds of interval estimates and the intervals’ reliability to
estimate the population median (level of confidence or proportion of sample interval estimates
that trap the population median). Conclusions are drawn about these relationships through
computer simulations using the freely available statistical software SeeIt.
This lesson looks back at the graphs students previously studied as an introduction to this module. Students are also asked to interpret what a graph communicates. They are reminded that a graph is not only a representation of data but also a summary of a data story. Each of the graphs presented in the exercises are encountered in the lessons that follow in this module. This lesson asks students to start thinking about what the data indicate, how they might have been collected, and what they tell us.
Students estimate the mean and median of a distribution represented by a dot plot or a histogram. Students indicate that the mean is a reasonable description of a typical value for a distribution that is symmetrical, but the median is a better description of a typical value for a distribution that is skewed. Students interpret the mean as a balance point of a distribution. Students indicate that for a distribution in which neither the mean nor the median is a good description of a typical value, the mean still provides a description of the center of a distribution in terms of the balance point.
In this graph project students will create a statistical question, gather, analyze, and graph data either by hand or using technology.
Students use a statistics calculator to compute the mean and the standard deviation of a data set and compare the variability of data sets. Additionally, students continue to refine their knowledge of standard deviation and how it measures a typical deviation from the mean.
Math 1 Statistics Project to assess students' knowledge of basic statistical information, and how to analyze their data. Students will be asking 20 students (or more if so desired by teacher) a question of their choice from a provided list. Students will then use their data to find mean, median, mode, range, and outliers; create a histogram and a box and whisker plot; and analyze their data by answering reflection questions. This project can be used as a final assessment for a Math 1 statistics unit.
Math 1 Statistics Project to assess students' knowledge of basic statistical information, and how to analyze their data. Students will be asking 20 students (or more if so desired by teacher) a question of their choice from a provided list. Students will then use their data to find mean, median, mode, range, and outliers; create a histogram and a box and whisker plot; and analyze their data by answering reflection questions. This project can bse used as a final test grade for a Math 1 statistics unit.
Math 1 Statistics Project to assess students' knowledge of basic statistical information, and how to analyze their data. Students will be asking 20 students (or more if so desired by teacher) a question of their choice from a provided list. Students will then use their data to find mean, median, mode, range, and outliers; create a histogram and a box and whisker plot; and analyze their data by answering reflection questions. This project can bse used as a final test grade for a Math 1 statistics unit.
This lesson addresses what measure of variability is appropriate for a skewed data distribution. Students construct a box plot of the data using the 5-number summary and describe variability using the interquartile range.
This lesson unit is intended to help teachers assess how well students are able to interpret data using frequency graphs and box plots. In particular this unit aims to identify and help students who have difficulty figuring out the data points and spread of data from frequency graphs and box plots. It is advisable to use the lesson: Representing Data 1: Frequency Graphs, before this one.
The lesson prepares students for a future understanding of the standard deviation of a data set, focusing on the role of the deviations from the mean. Students practice calculating deviations from the mean and generalize their calculations by relating them to the expression ?? - ??¯. Students reflect on the relationship between the sizes of the deviations from the mean and the spread (variability) of the distribution.