Course Project
Unit Goals
The goal of this unit is to have students work with data in a real context to understand various topics in statistics. This unit is designed to walk students through the statistical processing by formulating a statistical questions, finding descriptive statistics, comparing distributions, and making inferences
Scenario
Mrs. Jones is a geometry teacher at a high school with a traditional bell schedule. She teaches 6 periods of geometry each day. All of her students recently took a geometry test. Prior to starting their test, each student is asked to write the number of hours they studied for the test on the top of the test. The students then took the test and Mrs. Jones scored each test using a rubric. While handing the graded tests back, a student asked “Who did better? Boys or girls?” Mrs. Jones replied, “Well, I don’t know.” Later that night she created a spreadsheet with gender, hours studied, and test grades. She presented the aggregated data to her students and them the same question “Who did better? Boys or girls?”
Activities
Introduction: Introduces students to statistics vocabulary
Activity 1: Students use TI-84, TI-30XS, or Excel software to compare measures of center and measures of spread.
Activity 2: Students use graphing calculators to compare visual representations of two data sets.
Activity 3: Students use Excel to compare how two data sets are related.
The goal of this unit is to have students work with data in a real context to understand various topics in statistics. This unit is designed to walk students through the statistical processing by formulating a statistical questions, finding descriptive statistics, comparing distributions, and making inferences
Scenario
Mrs. Jones is a geometry teacher at a high school with a traditional bell schedule. She teaches 6 periods of geometry each day. All of her students recently took a geometry test. Prior to starting their test, each student is asked to write the number of hours they studied for the test on the top of the test. The students then took the test and Mrs. Jones scored each test using a rubric. While handing the graded tests back, a student asked “Who did better? Boys or girls?” Mrs. Jones replied, “Well, I don’t know.” Later that night she created a spreadsheet with gender, hours studied, and test grades. She presented the aggregated data to her students and them the same question “Who did better? Boys or girls?”
Activities
Introduction: Introduces students to statistics vocabulary
Activity 1: Students use TI-84, TI-30XS, or Excel software to compare measures of center and measures of spread.
Activity 2: Students use graphing calculators to compare visual representations of two data sets.
Activity 3: Students use Excel to compare how two data sets are related.
Unit Content Standards
6th grade
Mathematics Common Core Performance Standards 9-12. (2012). Retrieved June 1, 2015, from
https://www.georgiastandards.org/Common-Core/Pages/Math-9-12.aspx
6th grade
- MCC6.SP.1 Recognize a statistical question as one that anticipates variability in the data related
- MCC6.SP.2 Understand that a set of data collected to answer a statistical question has a distribution which can be described by its center, spread, and overall shape.
- MCC6.SP.3 Recognize that a measure of center for a numerical data set summarizes all of its values with a single number, while a measure of variation describes how its values vary with a single number.
- MCC6.SP.4 Display numerical data in plots on a number line, including dot plots, histograms, and box plots.
- MCC6.SP.5 Summarize numerical data sets in relation to their context
- MCC7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the centers by expressing it as a multiple of a measure of variability.
- MCC7.SP.4 Use measures of center and measures of variability for numerical data from random samples to draw informal comparative inferences about two populations.
- MCC8.SP.1 Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.
- MCC8.SP.2 Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line.
- MCC9‐12.S.ID.1 Represent data with plots on the real number line (dot plots, histograms, and box plots).
- MCC9‐12.S.ID.2 Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.
- MCC9‐12.S.ID.3 Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).
- MCC9‐12.S.ID.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.
- MCC9‐12.S.ID.7 Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.
- MCC9‐12.S.ID.8 Compute (using technology) and interpret the correlation coefficient of a linear fit
- MCC9‐12.S.ID.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.
- MCC9‐12.S.ID.2 Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.
- MSRFQ1. Students will apply the statistical method to real-world situations.
- MSRAD1. Students will use distributions to identify the key features of the data collected.
- MSRAD2. Students will use distributions to compare two or more groups
- MSRAD3. Students will determine if an association exists between two variables (pattern or trend in bivariate data) and use values of one variable to predict values of another variable.
- Make sense of problems and persevere in solving them.
- Reason abstractly and quantitatively.
- Construct viable arguments and critique the reasoning of others.
- Model with mathematics.
- Use appropriate tools strategically.
- Attend to precision.
Mathematics Common Core Performance Standards 9-12. (2012). Retrieved June 1, 2015, from
https://www.georgiastandards.org/Common-Core/Pages/Math-9-12.aspx