The Course includes the concept of probability distribution mainly binomial, poisson and normal distribution. In this course students will understood how to solve probability distribution problems using definition and open source software's like GeoGebra and excel

Students use latex tubes and bicycle pumps to conduct experiments to gather data about the relationship between latex strength and air pressure. Then they use this data to extrapolate latex strength to the size of latex tubing that would be needed in modern passenger sedans to serve as hybrid vehicle accelerators, thus answering the engineering design challenge question posed in the first lesson of this unit. Students input data into Excel spreadsheets and generate best fit lines by the selection of two data points from their experimental research data. They discuss the y-intercept and slope as it pertains to the mathematical model they generated. Students use the slope of the line to interpret the data collected. Then they extrapolate with this information to predict the latex dimensions that would be required for a full-size hydraulic accumulator installed in a passenger vehicle.

Students apply high school-level differential calculus and physics to the design of two-dimensional roller coasters in which the friction force is considered, as explained in the associated lesson. In a challenge the mirrors real-world engineering, the designed roller coaster paths must be made from at least five differentiable functions that are put together such that the resulting piecewise curving path is differentiable at all points. Once designed mathematically, teams build and test small-sized prototype models of the exact designs using foam pipe wrap insulation as the roller coaster track channel with marbles as the ride carts.

This lesson allows students to incorporate wearable technology to gather data that can later be used to reinforce Microsoft Excel skills.

This module contains the following units

Module 1: Basic ICT Skills

Unit 1: Know your device
Unit 2: Introduction to word processing as a teaching tool
Unit 3: Using a presentation package for teaching
Unit 4: Use a spreadsheet as a mark book
Unit 5: Internet, search engines, and curriculum resources
Unit 6: Social media to support teaching

In this activity, students will analyze raw data obtained from an experiment that explores the effect of overexpressing the Ssk protein in order to strengthen the intestinal barrier and prevent bacteria from leaking out of the gut and into the hemolymph, which is the fruit fly equivalent to blood in the circulatory system. Using Excel, students will fit an exponential function to the few known data points and will then interpolate the missing data points and extrapolate a few future data points. They will also learn how they can fit a linear model by transforming the data (applying the logarithmic function) and use that model to estimate the missing data points. This activity involves both statistical analysis and mathematical modeling as well as displaying the usefulness of mathematical models for biological data analysis.

Quantitative Research Methods for Political Science, Public Policy and Public Administration for Undergraduates: 1st Edition With Applications in Excel is an adaption of Quantitative Research Methods for Political Science, Public Policy and Public Administration (With Applications in R). The focus of this book is on using quantitative research methods to test hypotheses and build theory in political science, public policy and public administration. This new version is designed specifically for undergraduate courses. It omits large portions of the original text that focused on calculus and linear algebra, expands and reorganizes the content on the software system by shifting to Excel and includes guided study questions at the end of each chapter.

Students are introduced to the technology of flexible circuits, some applications and the photolithography fabrication process. They are challenged to determine if the fabrication process results in a change in the circuit dimensions since, as circuits get smaller and smaller (nano-circuits), this could become very problematic. The lesson prepares students to conduct the associated activity in which they perform statistical analysis (using Excel® and GeoGebra) to determine if the circuit dimension sizes before and after fabrication are in fact statistically different. A PowerPoint® presentation and post-quiz are provided. This lesson and its associated activity are suitable for use during the last six weeks of the AP Statistics course; see the topics and timing note for details.

Students apply pre-requisite statistics knowledge and concepts learned in an associated lesson to a real-world state-of-the-art research problem that asks them to quantitatively analyze the effectiveness of different cracked steel repair methods. As if they are civil engineers, students statistically analyze and compare 12 sets of experimental data from seven research centers around the world using measurements of central tendency, five-number summaries, box-and-whisker plots and bar graphs. The data consists of the results from carbon-fiber-reinforced polymer patched and unpatched cracked steel specimens tested under the same stress conditions. Based on their findings, students determine the most effective cracked steel repair method, create a report, and present their results, conclusions and recommended methods to the class as if they were presenting to the mayor and city council. This activity and its associated lesson are suitable for use during the last six weeks of the AP Statistics course; see the topics and timing note for details.

Working as if they are engineers aiming to analyze and then improve data collection devices for precision agriculture, students determine how accurate temperature sensors are by comparing them to each other. Teams record soil temperature data during a class period while making changes to the samples to mimic real-world crop conditions—such as the addition of water and heat and the removal of the heat. Groups analyze their collected data by finding the mean, median, mode, and standard deviation. Then, the class combines all the team data points in order to compare data collected from numerous devices and analyze the accuracy of their recording devices by finding the standard deviation of temperature readings at each minute. By averaging the standard deviations of each minute’s temperature reading, students determine the accuracy of their temperature sensors. Students present their findings and conclusions, including making recommendations for temperature sensor improvements.

Students build on their existing air quality knowledge and a description of a data set to each develop a hypothesis around how and why air pollutants vary on a daily and seasonal basis. Then they are guided by a worksheet through an Excel-based analysis of the data. This includes entering formulas to calculate statistics and creating plots of the data. As students complete each phase of the analysis, reflection questions guide their understanding of what new information the analysis reveals. At activity end, students evaluate their original hypotheses and “put all of the pieces together.” The activity includes one carbon dioxide worksheet/data set and one ozone worksheet/data set; providing students and/or instructors with a content option. The activity also serves as a good standalone introduction to using Excel.

In this activity students will use statistics and regression models to explore the effects of carbon dioxide on blood pH by measuring pH changes that occur over time as carbon dioxide reacts with water to form carbonic acid. Physiological pH changes caused by exercise are also examined.

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