Unit 1 - Exploring Real-Life Phenomena through statistics
Unit Description:
In this unit, students will be introduced to the study of statistics by experiencing how to design simple experiments and collect data. Students begin with learning what constitutes a statistical question. Students will have the opportunity to collect, analyze and display data through a number of graphical representations. Students will value how statistics affect daily life and the importance of being able to interpret how math represents world events by the end of this unit.
In this unit, students will be introduced to the study of statistics by experiencing how to design simple experiments and collect data. Students begin with learning what constitutes a statistical question. Students will have the opportunity to collect, analyze and display data through a number of graphical representations. Students will value how statistics affect daily life and the importance of being able to interpret how math represents world events by the end of this unit.
IN THIS UNIT, STUDENTS WILL:
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Khan Academy Resources
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Learning Objectives
6.NR.2.1 Describe and interpret the center of the distribution by the equal share value (mean).
6.NR.2.2 Summarize categorical and quantitative (numerical) data sets in relation to the context: display the distributions of quantitative (numerical) data in plots on a number line, including dot plots, histograms, and box plots and display the distribution of categorical data using bar graphs.
6.NR.2.3 Interpret numerical data to answer a statistical investigative question created. Describe the distribution of a quantitative (numerical) variable collected, including its center, variability, and overall shape.
6.NR.2.4 Design simple experiments and collect data. Use data gathered from realistic scenarios and simulations to determine quantitative measures of center (median and/or mean) and variability (interquartile range and range). Use these quantities to draw conclusions about the data, compare different numerical data sets, and make predictions.
6.NR.2.5 Relate the choice of measures of center and variability to the shape of the data distribution and the context in which the data were gathered.
6.NR.2.6 Describe the impact that inserting or deleting a data point has on the mean and the median of a data set. Create data displays using a dot plot or box plot to examine this impact.
6.NR.2.1 Describe and interpret the center of the distribution by the equal share value (mean).
6.NR.2.2 Summarize categorical and quantitative (numerical) data sets in relation to the context: display the distributions of quantitative (numerical) data in plots on a number line, including dot plots, histograms, and box plots and display the distribution of categorical data using bar graphs.
6.NR.2.3 Interpret numerical data to answer a statistical investigative question created. Describe the distribution of a quantitative (numerical) variable collected, including its center, variability, and overall shape.
6.NR.2.4 Design simple experiments and collect data. Use data gathered from realistic scenarios and simulations to determine quantitative measures of center (median and/or mean) and variability (interquartile range and range). Use these quantities to draw conclusions about the data, compare different numerical data sets, and make predictions.
6.NR.2.5 Relate the choice of measures of center and variability to the shape of the data distribution and the context in which the data were gathered.
6.NR.2.6 Describe the impact that inserting or deleting a data point has on the mean and the median of a data set. Create data displays using a dot plot or box plot to examine this impact.
I Can Statements:
- I can interpret the mean of a set of data.
- I can describe the center of distribution using mean.
- I can distinguish between categorical and numerical data.
- I can calculate measures of center for a data set (mean, median)
- I can calculate measures of variation from a data set (range, interquartile range, mean absolute deviation).
- I can create and analyze data in a box plot.
- I can identify and create statistical questions.
- I can identify an outlier in a set of data.
- I can describe the impact an outlier has on the mean and median for a set of data.
- I can make predictions using data gathered from realistic scenarios.
- I can determine the best measures of center and variation to describe data.
- I can analyze the shape of the data (i.e., narrow vs wide box, long vs short whisker)
Textbook Connections
Module 10 – Lesson 1 Statistical Questions
Students will identify and use statistical questions.
Module 10 – Lesson 2 Dot Plots and Histograms
Students will construct dot plots and histograms using collected data.
Module 10 – Lesson 3 Measures of Center
Students will understand and apply different measures of center.
Module 10 – Lesson 4 Interquartile Range and Box Plots
Students will understand interquartile range and construct box plots.
Module 10 – Lesson 5 Mean Absolute Deviation
Students will understand mean absolute deviation.
Module 10 – Lesson 6 Outliers
Students will understand outliers and their effect on measures of center.
Module 10 – Lesson 7 Interpret Graphical Displays
Students will interpret dot plots, histograms, and box plots.
Module 10 – Lesson 1 Statistical Questions
Students will identify and use statistical questions.
Module 10 – Lesson 2 Dot Plots and Histograms
Students will construct dot plots and histograms using collected data.
Module 10 – Lesson 3 Measures of Center
Students will understand and apply different measures of center.
Module 10 – Lesson 4 Interquartile Range and Box Plots
Students will understand interquartile range and construct box plots.
Module 10 – Lesson 5 Mean Absolute Deviation
Students will understand mean absolute deviation.
Module 10 – Lesson 6 Outliers
Students will understand outliers and their effect on measures of center.
Module 10 – Lesson 7 Interpret Graphical Displays
Students will interpret dot plots, histograms, and box plots.
IXL Unit Modules with Short Cut Codes
6.NR.2.1
Mean: Find the Missing Number - BCP
Calculate Mean - BK7
6.NR.2.2
Interpret Line Plots - M5Y
Create Line Plots - 5HD
Create and Interpret Line Plots with Fractions - QZP
Create Frequency Charts - W8X
Interpret Categorical Data - 59A
Create Relative Frequency Tables - 23P
Interpret Bar Graphs - UQA
Interpret Double Bar Graphs - GRP
Create Double Bar Graphs - DCY
Interpret Histograms - CBF
Create Histograms - 7NG
Box Plots - E9F
6.NR.2.3
Calculate Mean Absolute Deviation - JUV
Identify an Outlier - 86B
Interpret Measures of Center and Variability - PZB
Describe Distributions of Line Plots - RZL
6.NR.2.4
Interpret Charts and Graphs to find Mean, Median and Mode - 2WK
Interpret Median and Interquartile Range - Q2E
6.NR.2.1
Mean: Find the Missing Number - BCP
Calculate Mean - BK7
6.NR.2.2
Interpret Line Plots - M5Y
Create Line Plots - 5HD
Create and Interpret Line Plots with Fractions - QZP
Create Frequency Charts - W8X
Interpret Categorical Data - 59A
Create Relative Frequency Tables - 23P
Interpret Bar Graphs - UQA
Interpret Double Bar Graphs - GRP
Create Double Bar Graphs - DCY
Interpret Histograms - CBF
Create Histograms - 7NG
Box Plots - E9F
6.NR.2.3
Calculate Mean Absolute Deviation - JUV
Identify an Outlier - 86B
Interpret Measures of Center and Variability - PZB
Describe Distributions of Line Plots - RZL
6.NR.2.4
Interpret Charts and Graphs to find Mean, Median and Mode - 2WK
Interpret Median and Interquartile Range - Q2E